Awesome
<p align=center>Awesome Concealed Object Segmentation </p>
<p align=center>🔥A curated list of awesome <b>Concealed Object Segmentation(COS)</b> works.🔥</p> <p align=center>Please feel free to offer your suggestions in the Issues and pull requests to add links.</p> <p align=center><b>[ Last updated at 2024/10/16 ]</b></p>Contents
<span id = "latest-works-recommended">Latest Works Recommended</span>
Leveraging Hallucinations to Reduce Manual Prompt Dependency in Promptable Segmentation ProMaC
<br/>Jian Hu, Jiayi Lin, Junchi Yan, Shaogang Gong<br/>NeurIPS, 2024. [Paper] [Code]<br/>Sep. 2024
A Survey of Camouflaged Object Detection and Beyond <br/>Fengyang Xiao, Sujie Hu, Yuqi Shen, Chengyu Fang, Jinfa Huang, Chunming He, Longxiang Tang, Ziyun Yang, Xiu Li<br/>arxiv, 2024. [Paper] [Code]<br/>Aug. 2024
<span id = "Citation">Citation</span>
If you find our work useful in your research, please consider citing:
@article{2024CODsurvey,
title={A Survey of Camouflaged Object Detection and Beyond},
author={Xiao, Fengyang and Hu, Sujie and Shen, Yuqi and Fang, Chengyu and Huang, Jinfa and He, Chunming and Tang, Longxiang and Yang, Ziyun and Li, Xiu},
journal={arXiv preprint arXiv:2408.14562},
year={2024}
}
<span id = "papers">Papers</span>
<span id = "1-camouflaged-object-detectioncod">1. Camouflaged Object Detection(COD)</span>
<span id = "11-Image-level-COD">1.1 Image-level COD</span>
<span id = "111-Normal-task-setting">1.1.1 Normal-task setting</span>
Image-level COD methods in normal-task setting use a variety of different strategies, mainly in the following five categories. And we include tags related to core techniques for each item.
- Multi-scale-context (MSC)
- Mechanism-simulation (MS)
- Multi-source information fusion (MSI)
- Multi-task learning (MTL)
- Joint-SOD (JS)
<span id = "RGB-COD">1.1.1.1 RGB COD</span>
Release | Method | <br />Title | Pub. | Links |
---|---|---|---|---|
2024/09 | MM-CamObj<br />MSI MTL | MM-CamObj: A Comprehensive Multimodal Dataset for Camouflaged Object Scenarios<br/>MM-CamObj dataset <sup><sub>Jiacheng Ruan, Wenzhen Yuan, Zehao Lin, Ning Liao, Zhiyu Li, Feiyu Xiong, Ting Liu, Yuzhuo Fu</sub></sup> | arXiv<br />2024 | Paper |
2024/09 | FGSA-Net<br />MSC MSI | Frequency-Guided Spatial Adaptation for Camouflaged Object Detection<br/><sup><sub>Shizhou Zhang, Dexuan Kong, Yinghui Xing, Yue Lu, Lingyan Ran, Guoqiang Liang, Hexu Wang, Yanning Zhang</sub></sup> | TMM<br />2024 | Paper |
2024/09 | GLCONet<br />MSC | GLCONet: Learning Multi-source Perception Representation for Camouflaged Object Detection<br/><sup><sub>Yanguang Sun, Hanyu Xuan, Jian Yang, Lei Luo</sub></sup> | TNNLS<br />2024 | Paper/Code |
2024/09 | FSEL<br />MSC MSI | Frequency-Spatial Entanglement Learning for Camouflaged Object Detection<br/><sup><sub>Yanguang Sun, Chunyan Xu, Jian Yang, Hanyu Xuan, Lei Luo</sub></sup> | ECCV<br />2024 | Paper/Code |
2024/09 | SDRNet<br />MSC MTL | SDRNet: Camouflaged object detection with independent reconstruction of structure and detail<br/><sup><sub>Juwei Guan, Xiaolin Fang, Tongxin Zhu, Weiqi Qian</sub></sup> | KBS<br/>2024 | Paper/Code |
2024/08 | ProMaC<br />MSC MSI | Leveraging Hallucinations to Reduce Manual Prompt Dependency in Promptable Segmentation<br/><sup><sub>Jian Hu, Jiayi Lin, Junchi Yan, Shaogang Gong</sub></sup> | NeurIPS<br />2024 | Paper/Code |
2024/08 | ACUMEN<br />MSI MTL | Unlocking Attributes' Contribution to Successful Camouflage: A Combined Textual and Visual Analysis Strategy<br/>COD-TAX dataset <sup><sub>Hong Zhang, Yixuan Lyu, Qian Yu, Hanyang Liu, Huimin Ma, Ding Yuan, Yifan Yang</sub></sup> | ECCV<br />2024 | Paper/Code |
2024/08 | PSCOD<br />MSC MS | Just a Hint: Point-Supervised Camouflaged Object DetectionP-COD dataset <br/><sup><sub>Huafeng Chen, Dian Shao, Guangqian Guo, Shan Gao</sub></sup> | ECCV<br />2024 | Paper |
2024/08 | SAM-COD<br />MSC MSI | SAM-COD: SAM-guided Unified Framework for Weakly-Supervised Camouflaged Object Detection<br/><sup><sub>Huafeng Chen, Pengxu Wei, Guangqian Guo, Shan Gao</sub></sup> | ECCV<br />2024 | Paper |
2024/08 | CamoTeacher<br />MSI | CamoTeacher: Dual-Rotation Consistency Learning for Semi-Supervised Camouflaged Object Detection<br/><sup><sub>Xunfa Lai, Zhiyu Yang, Jie Hu, Shengchuan Zhang, Liujuan Cao, Guannan Jiang, Zhiyu Wang, Songan Zhang, Rongrong Ji</sub></sup> | ECCV<br />2024 | Paper |
2024/08 | IdeNet<br />MSC MS | IdeNet: Making Neural Network Identify Camouflaged Objects Like Creatures<br/><sup><sub>Juwei Guan; Xiaolin Fang; Tongxin Zhu; Zhipeng Cai; Zhen Ling; Ming Yang; Junzhou Luo</sub></sup> | TIP<br />2024 | Paper/Code |
2024/08 | MCA-SAM<br />Adaptor | Multi-scale Contrastive Adaptor Learning for Segmenting Anything in Underperformed Scenes<br/><sup><sub>Ke Zhou, Zhongwei Qiu, Dongmei Fu</sub></sup> | Neurocomputing<br /> 2024 | Paper |
2024/08 | HGINet<br /><br />MSC | Hierarchical Graph Interaction Transformer with Dynamic Token Clustering for Camouflaged Object Detection<br/><sup><sub>Siyuan Yao, Hao Sun, Tian-Zhu Xiang, Xiao Wang, Xiaochun Cao</sub></sup> | TIP<br />2024 | Paper/Code |
2024/08 | SAM2-UNet<br />MSC | SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation<br/><sup><sub>Xinyu Xiong, Zihuang Wu, Shuangyi Tan, Wenxue Li, Feilong Tang, Ying Chen, Siying Li, Jie Ma, Guanbin Li</sub></sup> | arXiv<br />2024 | Paper/Code |
2024/08 | SAM2-Adapter<br />Adapter | SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More<br/><sup><sub>Tianrun Chen, Ankang Lu, Lanyun Zhu, Chaotao Ding, Chunan Yu, Deyi Ji, Zejian Li, Lingyun Sun, Papa Mao, Ying Zang</sub></sup> | CoRR<br />2024 | Paper |
2024 | DCPNet<br />MSC MTL | Dual cross perception network with texture and boundary guidance for camouflaged object detection<br/><sup><sub>Yaming Wang, Jiatong Chen, Xian Fang, Mingfeng Jiang, Jianhua Ma</sub></sup> | CVIU<br/>2024 | Paper |
2024/07 | Technical Report | Evaluating SAM2's Role in Camouflaged Object Detection: From SAM to SAM2<br/><sup><sub>Lv Tang, Bo Li</sub></sup> | arXiv<br />2024 | Paper/Code |
2024/07 | WSSCOD<br />MSC MSI | Learning Camouflaged Object Detection from Noisy Pseudo Label<br/><sup><sub>Jin Zhang, Ruiheng Zhang, Yanjiao Shi, Zhe Cao, Nian Liu, Fahad Shahbaz Khan</sub></sup> | ECCV<br />2024 | Paper |
2024/07 | FocusDiffuser<br />Diffusion Model | FocusDiffuser: Perceiving Local Disparities for Camouflaged Object Detection<br/><sup><sub>Jianwei Zhao, Xin Li, Fan Yang, Qiang Zhai, Ao Luo, Zicheng Jiao, Hong Cheng</sub></sup> | ECCV<br />2024 | Paper/Code |
2024/05 | Spider<br />MSI MTL | Spider: A Unified Framework for Context-dependent Concept Segmentation<br/><sup><sub>Xiaoqi Zhao, Youwei Pang, Wei Ji, Baicheng Sheng, Jiaming Zuo, Lihe Zhang, Huchuan Lu</sub></sup> | ICML<br />2024 | Paper/Code |
2024/05 | TJNet<br />MSC MS MTL | Two guidance joint network based on coarse map and edge map for camouflaged object detection<br/><sup><sub>Zhe Tang, Jing Tang, Dengpeng Zou, Junyi Rao & Fang Qi</sub></sup> | AI<br />2024 | Paper/Code |
2024/05 | GreenCOD<br />MSC | GreenCOD: A Green Camouflaged Object Detection Method<br/><sup><sub>Hong-Shuo Chen, Yao Zhu, Suya You, Azad M. Madni, C.-C. Jay Kuo</sub></sup> | arXiv<br />2024 | Paper/Project |
2024/05 | AGLNet<br />MSC MSI | Adaptive Guidance Learning for Camouflaged Object Detection<br/><sup><sub>Zhennan Chen, Xuying Zhang, Tian-Zhu Xiang, Ying Tai</sub></sup> | arXiv<br />2024 | Paper/Code |
2024/04 | FS-CDIS <br />MTL | The Art of Camouflage: Few-shot Learning for Animal Detection and Segmentation CAMO-FS dataset <br/><sup><sub>Thanh-Danh Nguyen, Anh-Khoa Nguyen Vu, Nhat-Duy Nguyen, Vinh-Tiep Nguyen, Thanh Duc Ngo, Thanh-Toan Do, Minh-Triet Tran, Tam V. Nguyen</sub></sup> | IEEE ACCESS<br/>2024 | Paper |
2024/04 | LAKE-RED<br />Diffusion Model | LAKE-RED: Camouflaged Images Generation by Latent Background Knowledge Retrieval-Augmented Diffusion<br/><sup><sub>Pancheng Zhao, Peng Xu, Pengda Qin, Deng-Ping Fan, Zhicheng Zhang, Guoli Jia, Bowen Zhou, Jufeng Yang</sub></sup> | CVPR<br />2024 | Paper/Code |
2024/04 | EANet<br />MSC MTL | Edge Attention Learning for Efficient Camouflaged Object Detection<br/> <sup><sub>Zijian Liu; Ping Jiang; Lixin Lin; Xiaoheng Deng</sub></sup> | ICASSP<br />2024 | Paper |
2024/03 | EPNet<br />MSC MSI MTL | Edge Perception Camouflaged Object Detection under Frequency Domain Reconstruction<br/> <sup><sub>Zijian Liu; Xiaoheng Deng; Ping Jiang; Conghao Lv; Geyong Min; Xin Wang</sub></sup> | TCSVT<br />2024 | Paper |
2024/02 | SENet<br />JS MTL | A Simple yet Effective Network based on Vision Transformer for Camouflaged Object and Salient Object Detection<br/> <sup><sub>Chao Hao, Zitong Yu, Xin Liu, Jun Xu, Huanjing Yue, Jingyu Yang</sub></sup> | arXiv<br />2024 | Paper/Code |
2024/02 | SCLoss<br />loss function | Spatial Coherence Loss for Salient and Camouflaged Object Detection and Beyond<br/> <sup><sub>Ziyun Yang, Kevin Choy, Sina Farsiu</sub></sup> | arXiv<br />2024 | Paper |
2024/02 | CoFiNet<br />MSC | CoFiNet: Unveiling Camouflaged Objects with Multi-Scale Finesse<br/> <sup><sub>Cunhan Guo, Heyan Huang</sub></sup> | arXiv<br />2024 | Paper |
2024/02 | CCGNet<br />MSC MTL | Camouflaged Object Detection That Does Not Require Additional Priors<br/> <sup><sub>Yuchen Dong,Heng Zhou,Chengyang Li,Junjie Xie,Yongqiang Xie and Zhongbo Li</sub></sup> | Appl. Sci<br />2024 | Paper |
2024/01 | HCM<br />MSC | Concealed Object Segmentation with Hierarchical Coherence Modeling<br/> <sup><sub>Fengyang Xiao, Pan Zhang, Chunming He, Runze Hu, Yutao Liu</sub></sup> | CAAI<br />2023 | Paper |
2024/01 | PRNet<br />MSC MS | Efficient Camouflaged Object Detection Network Based on Global Localization Perception and Local Guidance Refinement<br/> <sup><sub>Xihang Hu; Xiaoli Zhang; Fasheng Wang; Jing Sun; Fuming Sun</sub></sup> | TCSVT<br />2023 | Paper/Code |
2024/01 | DINet<br />MSC | Decoupling and Integration Network for Camouflaged Object Detection<br/> <sup><sub>Xiaofei Zhou; Zhicong Wu; Runmin Cong</sub></sup> | TMM<br />2024 | Paper |
2024/01 | CamoFocus<br />MSC MS | CamoFocus: Enhancing Camouflage Object Detection With Split-Feature Focal Modulation and Context Refinement <br/> <sup><sub>Abbas Khan, Mustaqeem Khan, Wail Gueaieb, Abdulmotaleb El Saddik, Giulia De Masi, Fakhri Karray</sub></sup> | WACV<br />2024 | Paper/Code |
2023/12 | GenSAM<br />MSI | Relax Image-Specific Prompt Requirement in SAM: A Single Generic Prompt for Segmenting Camouflaged Objects<br> <sup><sub>Jian Hu, Jiayi Lin, Weitong Cai, Shaogang Gong</sub></sup> | AAAI<br />2024 | Paper/Code/Project |
2023/11 | OWinCANet <br />MSC | Cross-level Attention with Overlapped Windows for Camouflaged Object Detection<br/> <sup><sub>Jiepan Li, Fangxiao Lu, Nan Xue, Zhuohong Li, Hongyan Zhang, Wei He</sub></sup> | arXiv<br />2023 | Paper |
2023/11 | VSCode<br />JS MSI | VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning<br/> <sup><sub>Ziyang Luo, Nian Liu, Wangbo Zhao, Xuguang Yang, Dingwen Zhang, Deng-Ping Fan, Fahad Khan, Junwei Han</sub></sup> | CVPR<br />2024 | Paper/Code |
2023/11 | CoVP<br />MS | Chain of Visual Perception: Harnessing Multimodal Large Language Models for Zero-shot Camouflaged Object Detection<br/> <sup><sub>Lv Tang, Peng-Tao Jiang, Zhihao Shen, Hao Zhang, Jinwei Chen, Bo Li</sub></sup> | ACM MM<br />2024 | Paper/Code |
2023/10 | FRINet<br />MSC MSI MTL | Frequency Representation Integration for Camouflaged Object Detection <br> <sup><sub>Chenxi Xie,Changqun Xia,Tianshu Yu,Jia Li</sub></sup> | ACM MM<br />2023 | Paper/Code |
2023/10 | CINet<br />MSC | Camouflaged object detection with counterfactual intervention <br> <sup><sub>Xiaofei Li, Hongying Li, Hao Zhou, Miaomiao Yu, Dong Chen, Shuohao Li, Jun Zhang</sub></sup> | Neuro<br />2023 | Paper |
2023/10 | PrObeD<br />Wrapper | PrObeD: Proactive Object Detection Wrapper<br/> <sup><sub>Vishal Asnani, Abhinav Kumar, Suya You, Xiaoming Liu</sub></sup> | NeurIPS<br />2023 | Paper/Code |
2023/10 | PFRNet<br />MSC | You Do Not Need Additional Priors in Camouflage Object Detection<br/> <sup><sub>Yuchen Dong, Heng Zhou, Chengyang Li, Junjie Xie, Yongqiang Xie, Zhongbo Li</sub></sup> | arXiv<br />2023 | Paper |
2023/09 | DCNet<br />MSC MS MTL | Dual-Constraint Coarse-to-Fine Network for Camouflaged Object Detection <br> <sup><sub>Guanghui Yue; Houlu Xiao; Hai Xie; Tianwei Zhou; Wei Zhou; Weiqing Yan; etc.</sub></sup> | TCSVT<br />2023 | Paper |
2023/08 | CMNet<br />MSC JS MTL | Finding Camouflaged Objects along the Camouflage Mechanisms <br> <sup><sub>Yang Yang; Qiang Zhang</sub></sup> | TCSVT<br />2023 | Paper |
2023/08 | FPNet<br />MSC MS MSI | Frequency Perception Network for Camouflaged Object Detection <br> <sup><sub>Runmin Cong, Mengyao Sun, Sanyi Zhang, Xiaofei Zhou, Wei Zhang, Yao Zhao</sub></sup> | ACM MM<br />2023 | Paper/Code |
2023/08 | diffCOD<br />Diffusion Model | Diffusion Model for Camouflaged Object Detection <br> <sup><sub>Zhennan Chen, Rongrong Gao, Tian-Zhu Xiang, Fan Lin</sub></sup> | ECAI<br />2023 | Paper/Code |
2023/08 | ZSCOD<br />MSC MTL | Zero-Shot Camouflaged Object Detection <br> <sup><sub>Haoran Li; Chun-Mei Feng; Yong Xu; Tao Zhou; Lina Yao; Xiaojun Chang</sub></sup> | TIP<br />2023 | Paper |
2023/08 | JCNet<br />MSC JS MTL | Camouflaged Object Segmentation Based on Joint Salient Object for Contrastive Learning <br> <sup><sub>Jiang, Xinhao aPopNetnd Cai, Wei and Ding, Yao and Wang, Xin and Hong, Danfeng and Yang, Zhiyong and Gao, Weijie</sub></sup> | TIM<br />2023 | Paper/Code |
2023/08 | Camouflageator-ICEG<br />MSC MS MTL | Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects<br/><sup><sub>Chunming He, Kai Li, Yachao Zhang, Yulun Zhang, Zhenhua Guo, Xiu Li, Martin Danelljan, Fisher Yu</sub></sup> | ICLR<br />2024 | Paper/Code |
2023/08 | PENet<br />MSC MS MTL | Locate, Refine and Restore: A Progressive Enhancement Network for Camouflaged Object Detection<br/><sup><sub>Xiaofei Li; Jiaxin Yang; Shuohao Li; Jun Lei; Jun Zhang; Dong Chen</sub></sup> | IJCAI<br />2023 | Paper |
2023/08 | ASBI<br />MSC MTL | Attention-induced semantic and boundary interaction network for camouflaged object detection<br/><sup><sub>Qiao Zhang, Xiaoxiao Sun, Yurui Chen, Yanliang Ge, Hongbo Bi</sub></sup> | CVIU<br />2023 | Paper/Code |
2023/08 | TSFNet<br />MSC MS | Ternary symmetric fusion network for camouflaged object detection<br/><sup><sub>Yang Deng, Jianxin Ma, Yajun Li, M. Zhang, L. Wang</sub></sup> | API<br />2023 | Paper |
2023/08 | CINet<br />MSC | A cross-level interaction network based on scale-aware augmentation for camouflaged object detection<br/><sup><sub>Ming Ma; Bangyong Sun</sub></sup> | TETCI<br />2023 | Paper |
2023/08 | CamoFourier<br />MSI MTL | Unveiling Camouflage: A Learnable Fourier-based Augmentation for Camouflaged Object Detection and Instance Segmentation<br/><sup><sub>Minh-Quan Le, Minh-Triet Tran, Trung-Nghia Le, Tam V. Nguyen, Thanh-Toan Do</sub></sup> | arXiv<br />2023 | Paper |
2023/08 | SCODE<br />MTL | Camouflaged Image Synthesis Is All You Need to Boost Camouflaged Detection<br/><sup><sub>Haichao Zhang, Can Qin, Yu Yin, Yun Fu</sub></sup> | arXiv<br />2023 | Paper |
2023/07 | EAMNet<br />MSC MTL | Edge-Aware Mirror Network for Camouflaged Object Detection <br> <sup><sub>Dongyue Sun, Shiyao Jiang, Lin Qi</sub></sup> | ICME<br />2023 | Paper/Code |
2023/07 | FDNet<br />MSC | Camouflaged Object Detection with Feature Grafting and Distractor Aware ACOD2K <br> <sup><sub>Yuxuan Song, Xinyue Li, Lin Qi</sub></sup> | ICME<br />2023 | Paper/Code |
2023/07 | MRRNet<br />MSC MS | Camouflaged Object Segmentation Based on Matching–Recognition–Refinement Network <br> <sup><sub>Xinyu Yan; Meijun Sun; Yahong Han; Zheng Wang</sub></sup> | TNNLS<br />2023 | Paper/Code |
2023/07 | UEDG<br />MTL | UEDG: Uncertainty-Edge Dual Guided Camouflage Object Detection <br> <sup><sub>Lyu, Yixuan and Zhang, Hong and Li, Yan and Liu, Hanyang and Yang, Yifan and Yuan, Ding</sub></sup> | TMM<br />2023 | Paper/Code |
2023/07 | UJSCOD-V2<br />MTL JS | Joint Salient Object Detection and Camouflaged Object Detection via Uncertainty-aware LearningUJSCOD extention <br> <sup><sub>Aixuan Li, Jing Zhang, Yunqiu Lv, Tong Zhang, Yiran Zhong, Mingyi He, Yuchao Dai</sub></sup> | arXiv<br />2023 | Paper/Code/Project |
2023/07 | PAD<br />MTL | Pre-train, Adapt and Detect: Multi-Task Adapter Tuning for Camouflaged Object Detection <br> <sup><sub>Yinghui Xing, Dexuan Kong, Shizhou Zhang, Geng Chen, Lingyan Ran, Peng Wang, Yanning Zhang</sub></sup> | arXiv<br />2023 | Paper |
2023/07 | PUENet<br />MSC MTL | Predictive Uncertainty Estimation for Camouflaged Object Detection <br> <sup><sub>Yi Zhang, Jing Zhang, Wassim Hamidouche, Olivier Deforges</sub></sup> | TIP<br />2023 | Paper/Code |
2023/07 | AGNet<br />MSC MS MTL | Alternate guidance network for boundary-aware camouflaged object detection<br/> <sup><sub>Jinhao Yu, Shuhan Chen, Lu Lu, Zeyu Chen, Xiuqi Xu, Xuelong Hu & Jinrong Zhu</sub></sup> | MVA<br />2023 | Paper |
2023/06 | OPNet<br />MSC MS | Camouflaged Object Segmentation with Omni Perception <br> <sup><sub>Haiyang Mei, Ke Xu, Yunduo Zhou, Yang Wang, Haiyin Piao, Xiaopeng Wei, Xin Yang</sub></sup> | IJCV<br />2023 | Paper |
2023/06 | CFANet<br />MSC | CFANet: A Cross-layer Feature Aggregation Network for Camouflaged Object Detection <br> <sup><sub>Qing ZhangWeiqi Yan</sub></sup> | ICME<br />2023 | Paper/Code |
2023/06 | TinyCOD<br />MSC | TINYCOD: Tiny and Effective Model for Camouflaged Object Detection <br> <sup><sub>Haozhe Xing; Shuyong Gao; Hao Tang; Tsui Qin Mok; Yanlan Kang; Wenqiang Zhang</sub></sup> | ICASSP<br />2023 | Paper/Code |
2023/06 | OAFormer<br />MSC MS | OAFormer: Occlusion Aware Transformer for Camouflaged Object Detection <br> <sup><sub>Xin Yang, Hengliang Zhu, Guojun Mao, Shuli Xing</sub></sup> | ICME<br />2023 | Paper/Code |
2023/06 | Bi-RRNet<br />MSC | Bi-RRNet: Bi-level recurrent refinement network for camouflaged object detection<br> <sup><sub>Yan Liu, Kaihua Zhang, Yaqian Zhao, Hu Chen, Qingshan Liu</sub></sup> | PR<br />2023 | Paper |
2023/06 | CABR<br />MSC MTL | Camouflaged object detection based on context-aware and boundary refinement<br/> <sup><sub>Caijuan Shi, Bijuan Ren, Houru Chen, Lin Zhao, Chunyu Lin & Yao Zhao</sub></sup> | API<br />2023 | Paper |
2023/05 | WS-SAM <br />MSC | Weakly-Supervised Concealed Object Segmentation with SAM-based Pseudo Labeling and Multi-scale Feature Grouping<br/><sup><sub>Chunming He, Kai Li, Yachao Zhang, Guoxia Xu, Longxiang Tang, Yulun Zhang, Zhenhua Guo, Xiu Li</sub></sup> | NeurIPS<br />2023 | Paper/Code |
2023/05 | CamoDiffusion<br />Diffusion Model | CamoDiffusion: Camouflaged Object Detection via Conditional Diffusion Models <br> <sup><sub>Zhongxi Chen, Ke Sun, Xianming Lin, Rongrong Ji</sub></sup> | AAAI<br/>2024 | Paper/Code |
2023/05 | BTSNet<br />MSC MS MTL | A bioinspired three-stage model for camouflaged object detection<br/> <sup><sub>Tianyou Chen, Jin Xiao, Xiaoguang Hu, Guofeng Zhang, Shaojie Wang</sub></sup> | arXiv<br />2023 | Paper/Code |
2023/04 | FLCNet<br />MSC | Camouflaged Object Detection with a Feature Lateral Connection Network <br> <sup><sub>Tao Wang, Jian Wang, and Ruihao Wang</sub></sup> | Electronics<br />2023 | Paper/Code |
2023/04 | SAM-Adapter<br />Adapter | SAM Fails to Segment Anything? -- SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, and More <br> <sup><sub>Tianrun Chen, Lanyun Zhu, Chaotao Ding, Runlong Cao, Yan Wang, Zejian Li, Lingyun Sun, Papa Mao, Ying Zang</sub></sup> | arXiv<br />2023 | Paper |
2023/04 | BCNet<br />MSC MTL | Boundary-guided context-aware network for camouflaged object detection<br/> <sup><sub>J. Xiao, T. Chen, X. Hu, G. Zhang, S. Wang</sub></sup> | Neural Comput<br />2023 | Paper |
2023/04 | MFNet<br />MSC MTL | Edge-guided camouflaged object detection via multi-level feature integration<br/> <sup><sub>Kangwei Liu,Tianchi Qiu,Yinfeng Yu,Songlin Li, Xiuhong Li</sub></sup> | Sensors<br />2023 | Paper/Code |
2023/04 | DBFN<br />MSC | Double-branch fusion network with a parallel attention selection mechanism for camouflaged object detection <br/> <sup><sub>Junjiang Xiang, Qing Pan, Zhengrong Zhang, Songnian Fu & Yuwen Qin</sub></sup> | SCIS<br />2023 | Paper |
2023/04 | FSNet<br />MSC MS | FSNet: Focus Scanning Network for Camouflaged Object Detection<br> <sup><sub>Ze Song; Xudong Kang; Xiaohui Wei; Haibo Liu; Renwei Dian; Shutao Li</sub></sup> | TIP<br />2023 | Paper/Code |
2023/04 | CamDiff<br />Diffusion Model | CamDiff: Camouflage image augmentation via diffusion model<br/>Diff-COD dataset <sup><sub>Xue-Jing Luo, Shuo Wang, Zongwei Wu, Christos Sakaridis, Yun Cheng, Deng-Ping Fan, Luc Van Gool</sub></sup> | CAAI AIR<br />2023 | Paper/Code |
2023/04 | FS-CDIS<br />loss function | The Art of Camouflage: Few-Shot Learning for Animal Detection and SegmentationCAMO-FS dataset <br/><sup><sub>Thanh-Danh Nguyen, Anh-Khoa Nguyen Vu, Nhat-Duy Nguyen, Vinh-Tiep Nguyen, Thanh Duc Ngo, Thanh-Toan Do, Minh-Triet Tran, Tam V. Nguyen</sub></sup> | IEEE Access<br />2024 | Paper |
2023/04 | PFNet+<br />MSC MC | Distraction-aware camouflaged object segmentation<br/><sup><sub>Haiyang Mei, Xin Yang, Yunduo Zhou, Ge-Peng Ji, Xiaopeng Wei, and Deng-Ping Fan</sub></sup> | SSI<br />2023 | Code/Project |
2023/03 | Semi-SINet<br />MSC MS MTL | Camouflaged people detection based on a semi-supervised search identification network<br/> <sup><sub>Yang Liu, Cong-qing Wang, Yong-jun Zhou</sub></sup> | Def. Technol.<br />2023 | Paper |
2023/03 | SARNet<br />MSC MS | Go Closer To See Better: Camouflaged Object Detection via Object Area Amplification and Figure-ground Conversion <br> <sup><sub>Haozhe Xing; Yan Wang; Xujun Wei; Hao Tang; Shuyong Gao; Wenqiang Zhang</sub></sup> | TCSVT<br />2023 | Paper/Code |
2023/03 | SAT<br />JS | Nowhere to Disguise: Spot Camouflaged Objects via Saliency Attribute Transfer <br> <sup><sub>Wenda Zhao; Shigeng Xie; Fan Zhao; You He; Huchuan Lu</sub></sup> | TIP<br />2023 | Paper/Code |
2023/02 | MSCAF-Net<br />MSC MS | MSCAF-Net: A General Framework for Camouflaged Object Detection via Learning Multi-Scale Context-Aware Features <br> <sup><sub>Yu Liu; Haihang Li; Juan Cheng; Xun Chen</sub></sup> | TCSVT<br />2023 | Paper/Code |
2023/02 | FSPNet <br />MSC | Feature Shrinkage Pyramid for Camouflaged Object Detection with Transformers<br/><sup><sub>Zhou Huang, Hang Dai, Tian-Zhu Xiang, Shuo Wang, Huai-Xin Chen, Jie Qin, and Huan Xiong</sub></sup> | CVPR<br />2023 | Paper/Code |
2023/02 | FEDER <br />MSC MTL MSI | Camouflaged Object Detection with Feature Decomposition and Edge Reconstruction<br/><sup><sub>Chunming He, Kai Li, Yachao Zhang, Longxiang Tang, Yulun Zhang, Zhenhua Guo, Xiu Li</sub></sup> | CVPR<br />2023 | Paper/Code |
2023/02 | CPNet<br />MSC | Camouflaged Object Detection Based on Ternary Cascade Perception<br/><sup><sub>Xinhao Jiang,Wei Cai,Yao Ding, Xin Wang,Zhiyong Yang,Xingyu Di,Weijie Gao</sub></sup> | RS<br />2023 | Paper |
2022/12 | CamoFormer <br />MSC | CamoFormer: Masked separable attention for camouflaged object detection <br><sup><sub>BoFEDERwen Yin, Xuying Zhang, Qibin Hou, Bo-Yuan Sun, Deng-Ping Fan, and Luc Van Gool</sub></sup> | TPAMI<br/>2024 | Paper/Code |
2022/12 | AGFNet<br />MSC MTL | AGFNet: Attention Guided Fusion Network for Camouflaged Object Detection <br><sup><sub>Zeyu Zhao, Zhihao Liu & Chenglei Peng</sub></sup> | CICAI<br />2022 | Paper |
2022/12 | DQnet<br />MSC | DQnet: Cross-Model Detail Querying for Camouflaged Object Detection <br> <sup><sub>Wei Sun, Chengao Liu, Linyan Zhang, Yu Li, Pengxu Wei, Chang Liu, Jialing Zou, Jianbin Jiao, Qixiang Ye</sub></sup> | arXiv<br />2022 | Paper |
2022/11 | FAP-Net <br />MSC MTL | Feature Aggregation and Propagation Network for Camouflaged Object Detection <br><sup><sub>Tao Zhou, Yi Zhou, Chen Gong, Jian Yang, Yu Zhang</sub></sup> | TIP<br />2022 | Paper/Code |
2022/11 | DPSNet<br />MSC MTL | Boundary-aware Camouflaged Object Detection via Deformable Point Sampling <br> <sup><sub>Minhyeok Lee, Suhwan Cho, Chaewon Park, Dogyoon Lee, Jungho Lee, Sangyoun Lee</sub></sup> | ICEIC<br />2024 | Paper |
2022/11 | MGL-V2<br />MTL | MGL: Mutual Graph Learning for Camouflaged Object Detection CVPR21 (MGL) extension <br/> <sup><sub>Qiang Zhai; Xin Li; Fan Yang; Zhicheng Jiao; Ping Luo; Hong Cheng; Zicheng Liu</sub></sup> | TIP<br />2023 | Paper/Code |
2022/11 | TCU-Net<br />MSC | TCU-Net: Transformer and Convolutional Neural Network-Based Advanced U-Net for Concealed Object Detection<br/> <sup><sub>Kyeong-Beom Park; Jae Yeol Lee</sub></sup> | IEEE Access<br />2022 | Paper |
2022/10 | FindNet<br />MSC MS MTL | FindNet: Can You Find Me? Boundary-and-Texture Enhancement Network for Camouflaged Object Detection<br> <sup><sub>Peng Li, Xuefeng Yan, Hongwei Zhu, Mingqiang Wei, Xiao-Ping Zhang, Jing Qin</sub></sup> | TIP<br />2022 | Paper |
2022/10 | MFFN <br />MSC MS | MFFN: Multi-view Feature Fusion Network for Camouflaged Object Detection <br><sup><sub>Dehua Zheng, Xiaochen Zheng, Laurence T. Yang, Yuan Gao, Chenlu Zhu, Yiheng Ruan</sub></sup> | WACV<br />2023 | Paper/Code |
2022/10 | PreyNet <br />MSC MS MTL | PreyNet: Preying on camouflaged objects <br> <sup><sub>M Zhang, S Xu, Yongri Piao, D Shi, S Lin, H Lu</sub></sup> | ACM MM<br />2022 | Paper/Code |
2022/10 | ELDNet<br />MSC MTL | Eldnet: Establishment and Refinement of Edge Likelihood Distributions for Camouflaged Object Detection<br /><sup><sub>Chiyuan He; Linfeng Xu; Zihuan Qiu</sub></sup> | ICIP<br />2022 | Paper |
2022/09 | EINet<br />MSC | EINet: camouflaged object detection with pyramid vision transformer<br /><sup><sub>Chen Li, Ge Jiao</sub></sup> | JEI<br />2022 | Paper |
2022/09 | MAGNet<br />MSC MC | MAGNet: A Camouflaged Object Detection Network Simulating the Observation Effect of a Magnifier<br /><sup><sub>Xinhao Jiang,Wei Cai,Zhili Zhang,Bo Jiang,Zhiyong Yang andXin Wang</sub></sup> | Entropy<br />2022 | Paper/Code |
2022/08 | NCHIT<br />MSC | Camouflaged object detection via Neighbor Connection and Hierarchical Information Transfer<br /><sup><sub>Cong Zhang, Kang Wang, Hongbo Bi, Ziqi Liu, Lina Yang</sub></sup> | CVIU<br />2022 | Paper |
2022/07 | CRNet <br />MSC MS | Weakly-Supervised Camouflaged Object Detection with Scribble Annotations S-COD dataset <br><sup><sub>Ruozhen He, Qihua Dong, Jiaying Lin, Rynson W.H. Lau</sub></sup> | AAAI<br />2023 | Paper/Code |
2022/07 | PINet<br />MSC | Finding the Achilles Heel: Progressive Identification Network for Camouflaged Object Detection <br> <sup><sub>Mu-Chun Chou, Hung-Jen Chen, Hong-Han Shuai</sub></sup> | ICME<br />2022 | Paper/Code |
2022/07 | BGNet<br />MSC MTL | Boundary-Guided Camouflaged Object Detection <br> <sup><sub>Yujia Sun, Shuo Wang, Chenglizhao Chen, Tian-Zhu Xiang</sub></sup> | IJCAI<br />2022 | Paper/Code |
2022/07 | C2FNet-V2 <br />MSC | Camouflaged Object Detection via Context-aware Cross-level Fusion C2FNet Extension <br> <sup><sub>Geng Chen, Si-Jie Liu, Yu-Jia Sun, Ge-Peng Ji, Ya-Feng Wu, Tao Zhou</sub></sup> | TCSVT<br />2022 | Paper/Code |
2022/07 | DTC-Net <br />MSC | Deep Texton-Coherence Network for Camouflaged Object Detection <br> <sup><sub>Wei Zhai, Yang Cao, HaiYong Xie, Zheng-Jun Zha</sub></sup> | TMM<br />2022 | Paper |
2022/07 | BgNet<br />MSC MTL | Boundary-guided network for camouflage object detection <br> <sup><sub>Tianyou Chen, Jin Xiao, Xiaoguang Hu, Guofeng Zhang, Shaojie Wang</sub></sup> | KBS<br />2022 | Paper/Code |
2022/07 | CubeNet <br />MSC MTL | CubeNet: X-shape connection for camouflaged object detection <br> <sup><sub>Mingchen Zhuge, Xiankai Lu, Yiyou Guo, Zhihua Cai, Shuhan Chen</sub></sup> | PR<br />2022 | Paper/Code |
2022/07 | TPRNet<br />MSC | TPRNet: camouflaged object detection via transformer-induced progressive refinement network <br/> <sup><sub>Qiao Zhang, Yanliang Ge, Cong Zhang & Hongbo Bi</sub></sup> | TVC<br />2022 | Paper/Code |
2022/07 | ANSANet<br />MSC | Attention-based Neighbor Selective Aggregation Network for Camouflaged Object Detection <br/> <sup><sub>Yao Cheng; Hao-Zhou Hao; Yi Ji; Ying Li; Chun-Ping Liu</sub></sup> | IJCNN<br />2022 | Paper |
2022/07 | GMRNet<br />MSC MS | Guided multi-scale refinement network for camouflaged object detection <br/> <sup><sub>Xiuqi Xu, Shuhan Chen, Xiao Lv, Jian Wang & Xuelong Hu</sub></sup> | MTA<br />2022 | Paper |
2022/07 | DACFNet<br />MSC | Camouflaged Object Detection with Discriminative Information Attention and Cross-level Feature Fusion<br/> <sup><sub>Xinyue Li; Lin Li; Shiyao Jiang; Miao Yang; Lin Qi</sub></sup> | ICIVC<br />2022 | Paper |
2022/06 | FEMNet<br />MSC MSI | Detecting Camouflaged Object in Frequency Domain <br> <sup><sub>Yijie Zhong, Bo Li, Lv Tang, et al.</sub></sup> | CVPR<br />2022 | Paper |
2022/06 | BSA-Net <br />MSC MS MTL | I can find you! Boundary-guided Separated Attention Network for Camouflaged Object Detection <br><sup><sub>Hongwei Zhu, Peng Li, Haoran Xie, Mingqiang Wei, et al.</sub></sup> | AAAI<br />2022 | Paper/Code |
2022/06 | SegMaR <br />MSC MS | Segment, Magnify and Reiterate: Detecting Camouflaged Objects the Hard Way <br> <sup><sub>Qi Jia, S. Yao, Yu Liu, et al.</sub></sup> | CVPR<br />2022 | Paper/Code |
2022/06 | ZoomNet <br />MSC MS | Zoom In and Out: A Mixed-scale Triplet Network for Camouflaged Object Detection <br> <sup><sub>Youwei Pang, Xiaoqi Zhao, Tian-Zhu Xiang, Lihe Zhang, Huchuan Lu</sub></sup> | CVPR<br />2022 | Paper/Code |
2022/06 | FBNet <br />MSC MSI | Frequency-aware Camouflaged Object Detection <br> <sup><sub>Jiaying Lin, Xin Tan, Ke Xu, Lizhuang Ma, Rynson W.H. Lau</sub></sup> | TOMM<br />2022 | Paper |
2022/05 | DGNet<br />MSC MTL | Deep Gradient Learning for Efficient Camouflaged Object Detection <br><sup><sub>Ge-Peng Ji, Deng-Ping Fan, Yu-Cheng Chou, Dengxin Dai, Alexander Liniger, Luc Van Gool</sub></sup> | MIR<br />2023 | Paper/Code |
2022/05 | LSRNet-V2<br />MS MTL | Towards Deeper Understanding of Camouflaged Object Detection LSR extension <br> <sup><sub>Yunqiu Lv, Jing Zhang, Yuchao Dai, et al.</sub></sup> | TCSVT<br />2023 | Paper/Code |
2022/05 | DTINet<br />MS MTL | Boosting Camouflaged Object Detection with Dual-Task Interactive Transformer <br/> <sup><sub>Zhengyi Liu, Zhili Zhang, Wei Wu</sub></sup> | ICPR<br />2022 | Paper/Code |
2022/03 | HitNet <br />MSC | High-resolution Iterative Feedback Network for Camouflaged Object Detection <br> <sup><sub>Xiaobin Hu, Shuo Wang, Xuebin Qin, Hang Dai, Wenqi Ren, Donghao Luo, Ying Tai, Ling Shao</sub></sup> | AAAI<br />2023 | Paper/Code |
2022/03 | IIE-CIA<br />MSC MS | Toward Accurate Camouflaged Object Detection With In-Layer Information Enhancement and Cross-Layer Information Aggregation<br/> <sup><sub>Hongbo Bi; Cong Zhang; Kang Wang; Ranwan Wu</sub></sup> | TCDS<br />2022 | Paper |
2022/01 | OCENet<br />MSC MTL | Modeling Aleatoric Uncertainty for Camouflaged Object Detection <br> <sup><sub>Jiawei Liu, Jing Zhang, Nick Barnes</sub></sup> | WACV<br />2022 | Paper/Code |
2021/11 | ERRNet <br />MSC MS MTL | Fast Camouflaged Object Detection via Edge-based Reversible Re-calibration Network <br><sup><sub>Ge-Peng Ji, Lei Zhu, Mingchen Zhuge, Keren Fu</sub></sup> | PR<br />2022 | Paper/Code |
2021/11 | POCINet<br />MSC MS | Integrating Part-Object Relationship and Contrast for Camouflaged Object Detection <br><sup><sub>Yi Liu, Dingwen Zhang, Qiang Zhang, and Jungong Han</sub></sup> | TIFS<br />2021 | Paper/Code |
2021/10 | BgCod<br />MSC MTL | Boundary guidance network for camouflage object detection<br/><sup><sub>Xiuqi Xu, Mingyu Zhu, Jinhao Yu, Shuhan Chen, Xuelong Hu, Yuequan Yang</sub></sup> | IVC<br />2021 | Paper |
2021/10 | UR-COD<br />MTL | Improving Camouflaged Object Detection with the Uncertainty of Pseudo-edge Labels<br/><sup><sub>Nobukatsu Kajiura, Hong Liu, Shin'ichi Satoh</sub></sup> | ACM MM<br />2021 | Paper/Code |
2021/10 | UGTR <br />MTL | Uncertainty-Guided Transformer Reasoning for Camouflaged Object Detection <br><sup><sub>Fan Yang, Qiang Zhai, Xin Li, Rui Huang, et al.</sub></sup> | ICCV<br />2021 | Paper/Code |
2021/07 | CODCEF<br />MSC | Cascade and Fusion: A Deep Learning Approach for Camouflaged Object Sensing<br/><sup><sub>Kaihong Huang, ORCID,Chunshu Li, Jiaqi Zhang and Beilun Wang</sub></sup> | Sensors<br />2021 | Paper/Code |
2021/07 | ACDNet<br />MSC MS | ACDNet with ASPP for Camouflaged Object Detection<br/><sup><sub>Qihui Zhu</sub></sup> | ICAIIS<br />2021 | Paper |
2021/06 | UJSCOD <br />MTL JS | Uncertainty-aware Joint Salient Object and Camouflaged Object Detection <br><sup><sub>Aixuan Li, Jing Zhang, Yunqiu Lv, Bowen Liu, Tong Zhang, Yuchao Dai</sub></sup> | CVPR<br />2021 | Paper/Code |
2021/06 | LSRNet<br />MS MTL | Simultaneously Localize, Segment and Rank the Camouflaged Objects NC4K dataset <br><sup><sub>Yunqiu Lv, Jing Zhang, Yuchao Dai, Aixuan Li, et al.</sub></sup> | CVPR<br />2021 | Paper/Code |
2021/06 | PFNet <br />MSC MS | Camouflaged Object Segmentation with Distraction Mining <br><sup><sub>Haiyang Mei, Ge-Peng Ji, Ziqi Wei, Xin Yang, Xiaopeng Wei, Deng-Ping Fan</sub></sup> | CVPR<br />2021 | Paper/Code |
2021/06 | MGL <br />MTL | Mutual Graph Learning for Camouflaged Object Detection <br><sup><sub>Qiang Zhai, Xin Li, Fan Yang, Chenglizhao Chen, Hong Cheng, Deng-Ping Fan</sub></sup> | CVPR<br />2021 | Paper/Code |
2021/05 | C2FNet <br />MSC | Context-aware Cross-level Fusion Network for Camouflaged Object Detection <br><sup><sub>Yujia Sun, Geng Chen, Tao Zhou, Yi Zhang, Nian Liu</sub></sup> | IJCAI<br />2021 | Paper/Code |
2021/05 | TINet <br />MSC MTL | Inferring Camouflaged Objects by Texture-Aware Interactive Guidance Network <br><sup><sub>Jinchao Zhu, Xiaoyu Zhang, Shuo Zhang, Junnan Liu</sub></sup> | AAAI<br />2021 | Paper |
2021/05 | BASNet <br />MSC | Boundary-Aware Segmentation Network for Mobile and Web Applications <br> <sup><sub>Xuebin Qin, Deng-Ping Fan, Chenyang Huang, et al.</sub></sup> | arXiv<br />2021 | Paper/Code |
2021/03 | D2CNet<br />MSC MS | D2C-Net: A Dual-branch, Dual-guidance and Cross-refine Network for Camouflaged Object Detection <br><sup><sub>Kang Wang, Hongbo Bi, Yi Zhang, Cong Zhang, Ziqi Liu, Shuang Zheng</sub></sup> | TIE<br />2021 | Paper/Code |
2021/02 | SINet-V2 <br />MSC MS | Concealed Object Detection COD10K dataset <br><sup><sub>Deng-Ping Fan, Ge-Peng Ji, Ming-Ming Cheng, Ling Shao</sub></sup> | TPAMI<br />2022 | Paper/Code |
2021/02 | TANet <br />MSC | Deep Texture-Aware Features for Camouflaged Object Detection <br><sup><sub>Jingjing Ren, Xiaowei Hu, Lei Zhu, Xuemiao Xu, et al.</sub></sup> | TCSVT<br />2021 | Paper |
2021/01 | MCIF-Net <br />MSC | Accurate Camouflaged Object Detection via Mixture Convolution and Interactive Fusion <br> <sup><sub>Bo Dong, Mingchen Zhuge, Yongxiong Wang, Hongbo Bi, Geng Chen</sub></sup> | arXiv<br />2021 | Paper |
2020/07 | MirrorNet <br />MS | MirrorNet: Bio-Inspired Camouflaged Object Segmentation <br><sup><sub>Jinnan Yan, Trung-Nghia Le, Khanh-Duy Nguyen, Minh-Triet Tran, Thanh-Toan Do, Tam V. Nguyen</sub></sup> | IEEE Access<br />2021 | Paper/Project |
2020/04 | PDLF<br />Image Generation | Deep Camouflage Images<br><sup><sub>Qing Zhang, Gelin Yin, Yongwei Nie, Wei-Shi Zheng</sub></sup> | AAAI<br />2020 | Paper |
2020/06 | SINet<br />MSC MS | Camouflaged Object Detection COD10K dataset <br><sup><sub>Deng-Ping Fan, Ge-Peng Ji, Guolei Sun, Ming-Ming Cheng, Jianbing Shen, Ling Shao</sub></sup> | CVPR<br />2020 | Paper/Code |
2019/07 | ANet<br />MS MTL | Anabranch network for camouflaged object segmentation CAMO dataset <br><sup><sub>Trung-Nghia Le, Tam V. Nguyen, Zhongliang Nie, Minh-Triet Tran, Akihiro Sugimoto</sub></sup> | CVIU<br />2019 | Paper/Code/Project |
2018/04 | CPDDNet<br />MSC | Detection of People With Camouflage Pattern Via Dense Deconvolution Network CPD1K dataset <br><sup><sub>Yunfei Zheng, Xiongwei Zhang, Feng Wang, Tieyong Cao, Meng Sun, Xiaobing Wang</sub></sup> | SPL<br />2019 | Paper/Code |
<span id = "RGB-D-COD">1.1.1.2 RGB-D COD</span>
Release | Method | <br />Title | Pub. | Links |
---|---|---|---|---|
2024/07 | DSAM<br />MSI | Exploring Deeper! Segment Anything Model with Depth Perception for Camouflaged Object Detection<br/><sup><sub>Zhenni Yu, Xiaoqin Zhang, Li Zhao, Yi Bin, Guobao Xiao</sub></sup> | ACM MM<br />2024 | Paper/Code |
2024/05 | DAF-Net<br />MSC MSI | Depth Awakens: A Depth-perceptual Attention Fusion Network for RGB-D Camouflaged Object Detection<br/><sup><sub>Xinran Liua, Lin Qia, Yuxuan Songa, Qi Wen</sub></sup> | IVC<br />2024 | Paper/Code |
2024/04 | RISNet <br />MSC MSI | Depth-Aware Concealed Crop Detection in Dense Agricultural Scenes ACOD-12K dataset <br/> <sup><sub>Liqiong Wang, Jinyu Yang, Yanfu Zhang, Fangyi Wang, Feng Zheng</sub></sup> | CVPR<br />2024 | Paper/Code |
2023/10 | DaCOD<br />MSI | Depth-aided Camouflaged Object Detection <br> <sup><sub>Qingwei Wang,Jinyu Yang,Xiaosheng Yu,Fangyi Wang,Peng Chen,Feng Zheng</sub></sup> | ACM MM<br />2023 | Paper/Code |
2023/05 | XMSNet<br />MSC MSI | Object Segmentation by Mining Cross-Modal Semantics <br> <sup><sub>Zongwei Wu, Jingjing Wang, Zhuyun Zhou, Zhaochong An, Qiuping Jiang, Cédric Demonceaux, Guolei Sun, Radu Timofte</sub></sup> | ACM MM<br />2023 | Paper/Code |
2022/12 | PopNet<br />MSI | Source-free depth for object pop-out <br><sup><sub>Zongwei Wu, Danda Pani Paudel, Deng-Ping Fan, Jingjing Wang, Shuo Wang, Cédric Demonceaux, Radu Timofte, Luc Van Gool</sub></sup> | ICCV<br />2023 | Paper/Code |
2021/06 | DCE <br />MTL MSI | Exploring Depth Contribution for Camouflaged Object Detection <br> <sup><sub>Mochu Xiang, Jing Zhang, Yunqiu Lv, et al.</sub></sup> | arXiv<br />2021 | Paper |
<span id = "112-Novel-task-setting">1.1.2 Novel-task setting</span>
-
Unsupervised camouflaged object segmentation (UCOS)
-
Collaborative camouflaged object detection (CoCOD)
-
Referring camouflaged object detection (RefCOD)
-
Open-vocabulary camouflaged object segmentation (OVCOS)
Release | Method | Title | Pub. | Links | Task |
---|---|---|---|---|---|
2023/11 | OVCoser | Open-Vocabulary Camouflaged Object SegmentationOVCamo dataset <br/><sup><sub>Youwei Pang, Xiaoqi Zhao, Jiaming Zuo, Lihe Zhang, Huchuan Lu</sub></sup> | ECCV<br/>2024 | Paper | OVCOS |
2023/11 | MLKG | Large Model Based Referring Camouflaged Object Detection<br/><sup><sub>Shupeng Cheng, Ge-Peng Ji, Pengda Qin, Deng-Ping Fan, Bowen Zhou, Peng Xu</sub></sup> | arXiv<br />2023 | Paper | RefCOD |
2023/10 | BBNet<br /> | Collaborative Camouflaged Object Detection: A Large-Scale Dataset and Benchmark CoCOD8K dataset <br> <sup><sub>Cong Zhang, Hongbo Bi, Tian-Zhu Xiang, Ranwan Wu, Jinghui Tong, Xiufang Wang</sub></sup> | TNNLS<br />2023 | Paper/Code | CoCOD |
2023/06 | R2CNet | Referring Camouflaged Object Detection R2C7K dataset <br/><sup><sub>Xuying Zhang, Bowen Yin, Zheng Lin, Qibin Hou, Deng-Ping Fan, Ming-Ming Cheng</sub></sup> | arXiv<br />2023 | Paper/Code | RefCOD |
2023/08 | UCOS-DA | Unsupervised Camouflaged Object Segmentation as Domain Adaptation<br/> <sup><sub>Yi Zhang; Chengyi Wu</sub></sup> | ICCVW<br />2023 | Paper/Code | UCOS |
<span id = "12-Video-level-COD">1.2 Video-level COD(VCOD)</span>
<span id = "121-Novel-task-setting">1.2.1 Two-step framework</span>
Release | Method | Title | Pub. | Links |
---|---|---|---|---|
2023/09 | CAMEVAL | The Making and Breaking of Camouflage camouflage scores function <br> <sup><sub>Hala Lamdouar, Weidi Xie, Andrew Zisserman</sub></sup> | ICCV<br />2023 | Paper/Code |
2022/08 | OFS | EM-driven unsupervised learning for efficient motion segmentation <br> <sup><sub>Etienne Meunier, Ana¨ıs Badoual, and Patrick Bouthemy.</sub></sup> | TPAMI<br />2022 | Paper/Code |
2022/07 | OCLR | Segmenting Moving Objects via an Object-Centric Layered Representation <br> <sup><sub>Junyu Xie, Weidi Xie, Andrew Zisserman.</sub></sup> | NeurIPS<br />2022 | Paper |
2022/06 | SLTNet | Implicit Motion Handling for Video Camouflaged Object Detection MoCA-Mask dataset <br> <sup><sub>Xuelian Cheng, Huan Xiong, Deng-Ping Fan, et al.</sub></sup> | CVPR<br />2022 | Paper/Code |
2022/06 | QSDI | A Deeper Dive Into What Deep Spatiotemporal Networks Encode: Quantifying Static vs. Dynamic Information<br/> <sup><sub>Matthew Kowal, Mennatullah Siam, Md Amirul Islam, Neil D. B. Bruce, Richard P. Wildes, Konstantinos G. Derpanis</sub></sup> | CVPR<br />2022 | Paper/Code/Project |
2022/03 | RCF | The Right Spin: Learning Object Motion from Rotation-Compensated Flow Fields <br> <sup><sub>Pia Bideau, Erik Learned-Miller, Cordelia Schmid, et al.</sub></sup> | IJCV<br />2022 | Paper |
2021/11 | SIMO | Segmenting Invisible Moving Objects <br> <sup><sub>Hala Lamdouar, Weidi Xie, and Andrew Zisserman.</sub></sup> | BMVC<br />2021 | Paper/Project |
2021/04 | MG | Self-Supervised Video Object Segmentation by Motion Grouping <br> <sup><sub>Charig Yang, Hala Lamdouar, Erika Lu, et al.</sub></sup> | ICCV<br />2021 | Paper/Code/Project |
2020/11 | VRS | Betrayed By Motion: Camouflaged Object Discovery via Motion Segmentation MoCA dataset <br> <sup><sub>Hala Lamdouar, Charig Yang, Weidi Xie,et al.</sub></sup> | ACCV<br />2020 | Paper/Code |
2018/12 | FMC | Object discovery in videos as foreground motion clustering <br> <sup><sub>Christopher Xie, Yu Xiang, Zaid Harchaoui, et al.</sub></sup> | CVPR<br />2019 | Paper |
<span id = "122-End-to-end-framework">1.2.2 End-to-end framework</span>
Release | Method | Title | Pub. | Links |
---|---|---|---|---|
2024/06 | SAM-PM | SAM-PM: Enhancing Video Camouflaged Object Detection using Spatio-Temporal Attention<br/><sup><sub>Muhammad Nawfal Meeran, Gokul Adethya T, Bhanu Pratyush Mantha</sub></sup> | CVPR Ws<br />2024 | Paper/Code |
2024/03 | EMIP | Explicit Motion Handling and Interactive Prompting for Video Camouflaged Object Detection<br/><sup><sub>Xin Zhang, Tao Xiao, Gepeng Ji, Xuan Wu, Keren Fu, Qijun Zhao</sub></sup> | arXiv<br />2024 | Paper |
2024/02 | TSP-SAM | Endow SAM with Keen Eyes: Temporal-spatial Prompt Learning for Video Camouflaged Object Detection<br/> <sup><sub>Wenjun Hui, Zhenfeng Zhu, Shuai Zheng, Yao Zhao</sub></sup> | CVPR<br />2024 | Paper/Code |
2024/02 | IMEX | Implicit-Explicit Motion Learning for Video Camouflaged Object Detection<br/> <sup><sub>Wenjun Hui; Zhenfeng Zhu; Guanghua Gu; Meiqin Liu; Yao Zhao</sub></sup> | TMM<br />2024 | Paper |
2023/11 | TMNet | TokenMotion: Motion-Guided Vision Transformer for Video Camouflaged Object Detection Via Learnable Token Selection<br/> <sup><sub>Zifan Yu, Erfan Bank Tavakoli, Meida Chen, Suya You, Raghuveer Rao, Sanjeev Agarwal, Fengbo Ren</sub></sup> | ICASSP<br />2024 | Paper |
2023/10 | ZoomNeXt | ZoomNeXt: A Unified Collaborative Pyramid Network for Camouflaged Object Detection<br> <sup><sub>Youwei Pang, Xiaoqi Zhao, Tian-Zhu Xiang, Lihe Zhang, Huchuan Lu</sub></sup> | TPAMI<br />2024 | Paper/Code |
<span id = "2-transparent-object-segmentationtos">2. Transparent Object Segmentation(TOS)</span>
Release | Method | Title | Pub. | Links |
---|---|---|---|---|
2024/01 | - | Scanning and Affordance Segmentation of Glass and Plastic Bottles<br /><sup><sub>Floris Erich; Noriaki Ando; Yusuke Yoshiyasu</sub></sup> | SII<br />2024 | Paper |
2023/11 | CGSDNet | CGSDNet: Cascade Network with ConvNeXt as Backbone for Glass Surface Detection<br /><sup><sub>Zeyuan Chen; Masahiko Mikawa; Makoto Fujisawa</sub></sup> | ICAICA<br />2023 | Paper |
2023/06 | - | A Novel Transparent Object Detection Approach Based on Segmentation-Depth Reconstruction<br /><sup><sub>Zhonglin Li; Yang Luo; Yunxiang Jiang; Bi Zhang; Guoli Song; Xingang Zhao; Yiwen Zhao</sub></sup> | RCAR<br />2023 | Paper |
2023/06 | BCNet | Boundary Cue Guidance and Contextual Feature Mining for Glass Segmentation<br /><sup><sub>Qiquan Xiao; Yuan Zhang; Xuanya Li; Kai Hu</sub></sup> | ICASSP<br />2023 | Paper |
2023/03 | TROSNet | TROSD: A New RGB-D Dataset for Transparent and Reflective Object Segmentation in Practice<br /><sup><sub>Tianyu Sun; Guodong Zhang; Wenming Yang; Jing-Hao Xue; Guijin Wang</sub></sup> | TCSVT<br />2023 | Paper |
2022/04 | - | Glass Segmentation with RGB-Thermal Image Pairs<br /><sup><sub>Dong Huo, Jian Wang, Yiming Qian, Yee-Hong Yang</sub></sup> | TIP<br />2023 | Paper/Code |
2022/03 | ClearPose | ClearPose: Large-scale Transparent Object Dataset and Benchmark ClearPose dataset <br /><sup><sub>Xiaotong Chen, Huijie Zhang, Zeren Yu, Anthony Opipari, Odest Chadwicke Jenkins</sub></sup> | ECCV <br />2022 | Paper/Code |
2022/03 | Trans4Trans | Trans4Trans: Efficient Transformer for Transparent Object and Semantic Scene Segmentation in Real-World Navigation Assistance<br /><sup><sub>Jiaming Zhang; Kailun Yang; Angela Constantinescu; Kunyu Peng; Karin Müller; Rainer Stiefelhagen</sub></sup> | TITS<br />2022 | Paper |
2021/10 | - | Real-time Transparent Object Segmentation Based on Improved DeepLabv3+<sup><sub>Zhengguang Xu; Benshan Lai; Li Yuan; Tao Liu</sub></sup> | CAC<br />2021 | Paper |
2021/01 | Trans2Seg | Segmenting Transparent Object in the Wild with Transformer Trans10K-v2 dataset <br /><sup><sub>Enze Xie, Wenjia Wang, Wenhai Wang, Peize Sun, Hang Xu, Ding Liang, Ping Luo</sub></sup> | IJCAI<br />2021 | Paper/Code |
2020/06 | GDNet | Don’t Hit Me! Glass Detection in Real-world Scenes GDD dataset <br /><sup><sub>Haiyang Mei, Xin Yang, Yang Wang, Yuanyuan Liu, Shengfeng He, Qiang Zhang, Xiaopeng Wei, Rynson W.H. Lau</sub></sup> | CVPR<br />2020 | Paper/Code |
2020/06 | - | Deep Polarization Cues for Transparent Object Segmentation<br /><sup><sub>Agastya Kalra, Vage Taamazyan, Supreeth Krishna Rao, Kartik Venkataraman, Ramesh Raskar, Achuta Kadambi</sub></sup> | CVPR<br />2020 | Paper |
2020/05 | - | Single-Stage Semantic Segmentation from Image Labels<br /><sup><sub>Nikita Araslanov, Stefan Roth</sub></sup> | CVPR<br />2020 | Paper/Code |
2020/03 | TransLab | Segmenting Transparent Objects in the Wild Trans10K dataset <br /><sup><sub>Enze Xie, Wenjia Wang, Wenhai Wang, Mingyu Ding, Chunhua Shen, Ping Luo</sub></sup> | ECCV<br />2020 | Paper/Code |
2019/11 | - | Simultaneous Transparent and Non-Transparent Object Segmentation With Multispectral Scenes<br /><sup><sub>Atsuro Okazawa; Tomoyuki Takahata; Tatsuya Harada</sub></sup> | IROS<br />2019 | Paper |
2018/03 | TOM-Net | TOM-Net: Learning Transparent Object Matting from a Single Image TOM-Net dataset <br /><sup><sub>Guanying Chen, Kai Han, Kwan-Yee K. Wong</sub></sup> | CVPR<br />2018 | Paper/Code |
2015/11 | TransCut | TransCut: Transparent Object Segmentation from a Light-Field Image TransCut dataset <br /><sup><sub>Yichao Xu, Hajime Nagahara, Atsushi Shimada, Rin-ichiro Taniguchi</sub></sup> | ICCV<br />2015 | Paper |
2011/09 | - | Transparent object detection using color image and laser reflectance image for mobile manipulator<br /><sup><sub>Zhong Lei; Kazunori Ohno; Masanobu Tsubota; Eijiro Takeuchi; Satoshi Tadokoro</sub></sup> | ICRB<br />2011 | Paper |
<span id = "p_SDD">3. Surface Defect Detection(SDD)</span>
Release | Method | Title | Pub. | Links |
---|---|---|---|---|
2023/12 | - | Transformer and Feature Enhancement for Lightweight Rail Surface Defect Detection<br /><sup><sub>Baoqu Gao; Jing Peng</sub></sup> | ITAIC<br />2023 | Paper |
2023/11 | MFAM-Net | MFAM-Net:A Surface Defect Detection Network for Strip Steel via Multiscale Feature Fusion and Attention Mechanism<br /><sup><sub>Qingtian Zeng; Daibai Wei; Xue Zhang; Quan Gan; Qihong Wang; Minghao Zou</sub></sup> | NTCI<br />2023 | Paper |
2023/11 | - | Metal Surface Defect Detection Algorithm Based on Improved YOLOv5<br /><sup><sub>Xiaodong Su; Fengchun Zhang; Yurong Zhang; Hongyan Xu; Xu Chen</sub></sup> | ITOEC<br />2023 | Paper |
2023/09 | - | Improved Yolov5n strip surface defect detection algorithm<br /><sup><sub>Lin Tang; Le Cai Cai; Kui Cheng; Xinjie Wang; Chunlan Luo; Yunlong Zhao</sub></sup> | SAFEPROCESS<br />2023 | Paper |
2023/08 | - | Piano Wooden Parts Paint Surface Defect Detection based on YOLO<br /><sup><sub>Haoping Li; Zhuhong Jin; Ronghua Meng; Wei Peng; Liuyang Cai</sub></sup> | ICBAIE<br />2023 | Paper |
2023/03 | - | Design of Rail Surface Defect Detection System Based on LabVIEW Machine Vision<br /><sup><sub>Han Han; Liguo Tian; Meng Li; Xudong Cui; Chunhu Shang; Shidong Hou</sub></sup> | ITNEC<br />2023 | Paper |
2023/03 | - | A Tiny Defect Detection System for Tire Mold Surfaces Based on Consecutive Frames<br /><sup><sub>Yu-Hung Lin; Shanq-Jang Ruan</sub></sup> | TIM<br />2023 | Paper |
2022/09 | - | Surface Defect Detection of Aircraft Glass Canopy Based on Improved YOLOv4<br /><sup><sub>Jing Wang; Siwen Wei; Kexin Wang; Jianhong Li</sub></sup> | ISCIT<br />2022 | Paper |
2022/07 | - | A Deep Learning Based Surface Defect Detection Method with Coarse Granularity for Corrugated Fuel Tubes<br /><sup><sub>Zongze Wu; Zizhuo Zhang; Jun Xu; Qiang Ling</sub></sup> | CCC<br />2022 | Paper |
2022/07 | - | Surface Defect Detection of Steel Products Based on Improved YOLOv5<br /><sup><sub>Yajiao Liu; Jiang Wang; Haitao Yu; Fulong Li; Lifeng Yu; Chunhui Zhang</sub></sup> | CCC<br />2022 | Paper |
2022/06 | - | A Surface Fatal Defect Detection Method for Magnetic Tiles based on Semantic Segmentation and Object Detection<br /><sup><sub>Zedong Zhu; Peiyuan Zhu; Jiaxing Zeng; Xiang Qian</sub></sup> | ITAIC<br />2022 | Paper |
2021/03 | - | A Learning-Based Surface Defect Detection Method for Internal Surfaces of Bellows<br /><sup><sub>Zizhuo Zhang; Jun Xu; Song Wang; Feng Li; Qiang Ling</sub></sup> | CCDC<br />2021 | Paper |
2021/03 | - | Surface Defects Detection and Identification of Lithium Battery Pole Piece Based on Multi-Feature Fusion and PSO-SVM<br /><sup><sub>Changlu Xu; Linsheng Li; Jiwei Li; Chuanbo Wen</sub></sup> | IEEE Access | Paper |
2021/01 | - | A Detection and Identification Method Based on Machine Vision for Bearing Surface Defects<br /><sup><sub>Zhengyan Gu; Xiaohui Liu; Lisheng Wei</sub></sup> | ICCCR<br />2021 | Paper |
2020/10 | - | Sanitary Ceramic Surface Defect Detection Method Based on Neighborhood Pixel Gray Information<br /><sup><sub>Jingfan Hang; Xianqiang Yang; Xinghu Yu</sub></sup> | IECON<br />2020 | Paper |
2019/11 | - | A visual detection method of tile surface defects based on spatial-frequency domain image enhancement and region growing<br /><sup><sub>Guofeng Zou; Taotao Li; Guangya Li; Xiang Peng; Guixia Fu</sub></sup> | CAC<br />2019 | Paper |
2019/03 | - | Segmentation Based Deep-Learning Approach for Surface Defect Detection KolektorSDD dataset <br /><sup><sub>Domen Tabernik, Samo Šela, Jure Skvarč, Danijel Skočaj</sub></sup> | J Intell Manuf<br />2019 | Paper |
2018/09 | - | Fast Surface Defect Detection Using Improved Gabor Filters<br /><sup><sub>Jiaxu Ma; Yuxi Wang; Chen Shi; Cewu Lu</sub></sup> | ICIP<br />2018 | Paper |
2018/06 | - | Surface Defect Detection Based on Gradient LBP<br /><sup><sub>Xiaojing Liu; Feng Xue; Lu Teng</sub></sup> | ICIVC<br />2018 | Paper |
2012/10 | - | Unsupervised detection of surface defects: A two-step approach<br /><sup><sub>Jiwon Choi; Changick Kim</sub></sup> | ICIP<br />2012 | Paper |
<span id = "4-polyp-segmentationps">4. Polyp Segmentation(PS)</span>
Release | Method | Title | Pub. | Links |
---|---|---|---|---|
2024/01 | CCFNet | Cross-level Context Fusion Network for Polyp Segmentation in Colonoscopy Images<br /><sup><sub>Duanfang Cai; Kongcai Zhan; Youguo Tan; Xiaoyan Chen; Heng Luo; Guangyu Li</sub></sup> | IEEE Access | Paper |
2024/01 | DUSFormer | DUSFormer: Dual-Swin Transformer V2 Aggregate Network for Polyp Segmentation<br /><sup><sub>Zhangrun Xia; Jingliang Chen; Chengzhun Lu</sub></sup> | IEEE Access | Paper |
2023/12 | HybridVPS | HybridVPS: Hybrid-Supervised Video Polyp Segmentation Under Low-Cost Labels<br /><sup><sub>Wenxue Li; Xinyu Xiong; Siying Li; Fugui Fan</sub></sup> | SPL<br />2023 | Paper |
2023/12 | UDnet | UDnet: A Polyp Image Segmentation Method Based on Derivative Network<br /><sup><sub>Mengxin Li; Donghui Piao; Baofeng Wang</sub></sup> | ICEACE<br />2023 | Paper |
2023/12 | - | DeeplabV3+ Driven Polyp Segmentation: Advancing Colonoscopy Diagnosis<br /><sup><sub>Nabil Ahmed; MD. Naimujjaman; Mahbuba Akhter; Hasan Monir</sub></sup> | ICCIT<br />2023 | Paper |
2023/10 | S2ME | S2ME: Spatial-Spectral Mutual Teaching and Ensemble Learning for Scribble-Supervised Polyp Segmentation<br /><sup><sub>An Wang, Mengya Xu, Yang Zhang, Mobarakol Islam & Hongliang Ren</sub></sup> | MICCAI<br />2023 | Paper/Code |
2023/04 | - | Enhancing Polyp Segmentation Generalizability by Minimizing Images’ Total Variation<br /><sup><sub>Mahmood Haithami; Amr Ahmed; Iman Yi Liao; Hamid Jalab</sub></sup> | ISBI<br />2023 | Paper |
2023/04 | PST-Net | Unpaired Image-to-Image Translation Based Domain Adaptation for Polyp Segmentation<br /><sup><sub>Xinyu Xiong; Siying Li; Guanbin Li</sub></sup> | ISBI<br />2023 | Paper |
2023/04 | FPN | An Accurate Polyp Segmentation Framework via Feature Secondary Fusion<br /><sup><sub>Yanzhou Su; Qingsong Xie; Jin Ye; Junjun He; Jian Cheng</sub></sup> | ISBI<br />2023 | Paper |
2023/04 | - | Go To The Right: A Real-Time and Accurate Polyp Segmentation Model for Practical Use<br /><sup><sub>Yanzhou Su; Changjian Deng; Zhongying Deng; Jin Ye; Junjun He; Jian Cheng</sub></sup> | ISBI<br />2023 | Paper |
2022/09 | LDNet | Lesion-aware Dynamic Kernel for Polyp Segmentation<br /><sup><sub>Ruifei Zhang, Peiwen Lai, Xiang Wan, De-Jun Fan, Feng Gao, Xiao-Jian Wu & Guanbin Li</sub></sup> | MICCAI<br />2022 | Paper/Code |
2022/09 | SSFormer | Stepwise Feature Fusion: Local Guides Global<br /><sup><sub>Jinfeng Wang, Qiming Huang, Feilong Tang, Jia Meng, Jionglong Su & Sifan Song</sub></sup> | MICCAI<br />2022 | Paper/Code |
2022/09 | LDNet | Lesion-Aware Dynamic Kernel for Polyp Segmentation<br /><sup><sub>Ruifei Zhang, Peiwen Lai, Xiang Wan, De-Jun Fan, Feng Gao, Xiao-Jian Wu & Guanbin Li</sub></sup> | MICCAI<br />2022 | Paper/Code |
2022/09 | SSTAN | Semi-supervised Spatial Temporal Attention Network for Video Polyp Segmentation<br /><sup><sub>Xinkai Zhao, Zhenhua Wu, Shuangyi Tan, De-Jun Fan, Zhen Li, Xiang Wan & Guanbin Li</sub></sup> | MICCAI<br />2022 | Paper/Code |
2022/09 | TRFRNet | Task-Relevant Feature Replenishment for Cross-Centre Polyp Segmentation<br /><sup><sub>Task-Relevant Feature Replenishment for Cross-Centre Polyp Segmentation</sub></sup> | MICCAI<br />2022 | Paper/Code |
2022/09 | PPFormer | Using Guided Self-Attention with Local Information for Polyp Segmentation<br /><sup><sub>Linghan Cai, Meijing Wu, Lijiang Chen, Wenpei Bai, Min Yang, Shuchang Lyu & Qi Zhao</sub></sup> | MICCAI<br />2022 | Paper |
2022/09 | CPC-Trans | Toward Clinically Assisted Colorectal Polyp Recognition via Structured Cross-Modal Representation Consistency<br /><sup><sub>Weijie Ma, Ye Zhu, Ruimao Zhang, Jie Yang, Yiwen Hu, Zhen Li & Li Xiang</sub></sup> | MICCAI<br />2022 | Paper/Code |
2022/09 | CT | Contrastive Transformer-Based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection<br /><sup><sub>Yu Tian, Guansong Pang, Fengbei Liu, Yuyuan Liu, Chong Wang, Yuanhong Chen, Johan Verjans & Gustavo Carneiro</sub></sup> | MICCAI<br />2022 | Paper/Code |
2022/09 | BoxPolyp | BoxPolyp: Boost Generalized Polyp Segmentation Using Extra Coarse Bounding Box Annotations<br /><sup><sub>Jun Wei, Yiwen Hu, Guanbin Li, Shuguang Cui, S. Kevin Zhou & Zhen Li</sub></sup> | MICCAI<br />2022 | Paper |
2022/08 | BCNet | Boundary Constraint Network With Cross Layer Feature Integration for Polyp Segmentation<br/><sup><sub>Guanghui Yue, Wanwan Han, Bin Jiang, Tianwei Zhou, Runmin Cong, Tianfu Wang</sub></sup> | IEEE JHBI<br />2022 | Paper |
2022/05 | TGANet | TGANet: Text-Guided Attention for Improved Polyp Segmentation<br /><sup><sub>Nikhil Kumar Tomar, Debesh Jha, Ulas Bagci, Sharib Ali</sub></sup> | MICCAI<br />2022 | Paper/Code |
2022/03 | DCRNet | Duplex Contextual Relation Network For Polyp Segmentation<br /><sup><sub>Zijin Yin; Kongming Liang; Zhanyu Ma; Jun Guo</sub></sup> | ISBI<br />2022 | Paper/Code |
2022/03 | CoFo | Adversarial Contrastive Fourier Domain Adaptation for Polyp Segmentation<br /><sup><sub>Ta Duc Huy; Hoang Cao Huyen; Chanh D. T. Nguyen; Soan T. M. Duong; Trung Bui; Steven Q. H. Truong</sub></sup> | ISBI<br />2022 | [Paper]([Adversarial Contrastive Fourier Domain Adaptation for Polyp Segmentation )/Code |
2021/03 | AAU-Net | Asymmetric Attention Upsampling: Rethinking Upsampling For Biological Image Segmentation<br /><sup><sub>Chunyu Dong; Qunfei Zhao; Kun Chen; Xiaolin Huang</sub></sup> | ISBI<br />2021 | Paper |
2020/03 | SSN | SSN: A Stair-Shape Network for Real-Time Polyp Segmentation in Colonoscopy Images<br /><sup><sub>Ruiwei Feng; Biwen Lei; Wenzhe Wang; Tingting Chen; Jintai Chen; Danny Z. Chen; Jian Wu</sub></sup> | ISBI<br />2020 | Paper |
2019/04 | - | Polyp Tracking in Video Colonoscopy Using Optical Flow With an On-The-Fly Trained CNN<br /><sup><sub>Polyp Tracking in Video Colonoscopy Using Optical Flow With an On-The-Fly Trained CNN</sub></sup> | ISBI<br />2019 | Paper |
<span id = "5-lung-nodule-detectionlnd">5. Lung Nodule Detection(LND)</span>
Release | Method | Title | Pub. | Links |
---|---|---|---|---|
2023/10 | - | Detection and Localization of Lung Nodules by Accelerating Multi-dimensional Images using Graph Data Science<br /><sup><sub>Akhila Thejaswi R; Bellipady Shamantha Rai; Permanki Guthu Rithesh Pakkala; Niranjan Bhat; Nishanth V Poojary, etc.</sub></sup> | DISCOVER<br />2023 | Paper |
2023/08 | - | Lung Nodule Classification Using MobileNet Transfer Learning<br /><sup><sub>Rajdeep Ghosh; Adnan Ahamed; Bikash Sadhukhan; Nabanita Das</sub></sup> | ICSCC<br />2023 | Paper |
2023/04 | CdcSegNet | CdcSegNet: Automatic COVID-19 Infection Segmentation From CT Images<br /><sup><sub>Ju Zhang; Dechen Chen; Dong Ma; Changgang Ying; Xiaoyan Sun; Xiaobing Xu; Yun Cheng</sub></sup> | TIM<br />2023 | Paper |
2022/12 | MHSnet | MHSnet: Multi-head and Spatial Attention Network with False-Positive Reduction for Lung Nodule Detection<br /><sup><sub>Juanyun Mai; Minghao Wang; Jiayin Zheng; Yanbo Shao; Zhaoqi Diao; Xinliang Fu; Yulong Chen; Jianyu Xiao; Jian You; Airu Yin; Yang Yang; Xiangcheng Qiu; Jinsheng Tao;Bo Wang; Hua Ji</sub></sup> | BIBM<br />2022 | Paper |
2022/10 | - | A Coarse-to-Fine Morphological Approach with Knowledge-Based Rules and Self-Adapting Correction for Lung Nodules Segmentation<br /><sup><sub>Xinliang Fu; Jiayin Zheng; Juanyun Mai; Yanbo Shao; Minghao Wang; Linyu Li; Zhaoqi Diao; Yulong Chen; Jianyu Xiao, etc.</sub></sup> | ICIP<br />2022 | Paper |
2022/10 | RACN | Semi-Supervised Adversarial Learning for Improving the Diagnosis of Pulmonary Nodules<br /><sup><sub>Yu Fu; Peng Xue; Taohui Xiao; Zhili Zhang; Youren Zhang; Enqing Dong</sub></sup> | JBHI<br />2023 | Paper |
2022/09 | - | Multi-Label Softmax Networks for Pulmonary Nodule Classification Using Unbalanced and Dependent Categories<br /><sup><sub>Le Yi; Lei Zhang; Xiuyuan Xu; Jixiang Guo</sub></sup> | TMI<br />2023 | Paper |
2022/08 | LSSANet | LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection<br /><sup><sub>Rui Xu, Yong Luo, Bo Du, Kaiming Kuang, Jiancheng Yang</sub></sup> | MICCAI<br />2022 | Paper/Code |
2021/03 | SANet | SANet: A Slice-Aware Network for Pulmonary Nodule Detection PN9 dataset <br /><sup><sub>Domen Tabernik, Samo Šela, Jure Skvarč, Danijel Skočaj</sub></sup> | TPAMI<br />2021 | Paper/Code |
2020/01 | - | Detection and Recognition of Lung Nodules in Medical Images Using Chaotic Ant Colony Algorithm<br /><sup><sub>Jinxia Li; Hongbo Zhao; Yanni Yang</sub></sup> | ICMTMA<br />2020 | Paper |
2018/10 | MV-KBC | Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT<br /><sup><sub>Yutong Xie; Yong Xia; Jianpeng Zhang; Yang Song; Dagan Feng; Michael Fulham; Weidong Cai</sub></sup> | TMI<br />2019 | Paper |
2018/03 | DeepLung | DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification<br /><sup><sub>Wentao Zhu; Chaochun Liu; Wei Fan; Xiaohui Xie</sub></sup> | WACV<br />2018 | Paper |
2016/03 | ConvNets | Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks<br /><sup><sub>Arnaud Arindra Adiyoso Setio; Francesco Ciompi; Geert Litjens; Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, The Netherlands , etc. </sub></sup> | TMI<br />2016 | Paper |
2014/08 | - | Artificial neural network-based classification system for lung nodules on computed tomography scans<br /><sup><sub>Emre Dandıl; Murat Çakiroğlu; Ziya Ekşi; Murat Özkan; Özlem Kar Kurt; Arzu Canan</sub></sup> | SoCPaR<br />2014 | Paper |
<span id = "Datasets">Datasets</span>
<span id = "1-camouflaged-object-detectioncod-1">1. Camouflaged Object Detection(COD)</span>
The basic information of both image-level and video-level COD datasets.
- Level: data type of dataset, i.e., Image(I) and Video(V).
- Train/Test: number of samples for training/testing, e.g., images for image dataset or frames for video dataset.
- Resolution: image or frame resolution, some may be a range from the smallest area to the largest area.
- Objects
- object categories of datasets.
- **N. Cam. **: whether collecting non-camouflaged samples.
- Labels
- Cls.: whether providing classification labels for Camouflaged Objects Classification(COCls). If so, the number of categories are provided.
- Fix.: whether providing fixation annotation for Camouflaged Objects Localization(COL).
- B. Box: whether providing bounding box labels.
- Obj.: whether providing object-level segmentation masks.
- Ins.: whether providing instance-level segmentation masks for Camouflaged Instance Segmentation (CIS).
- Ran.: whether providing ranking labels for Camouflaged Instance Rank (CIR).
- Scr.: whether providing weakly-supervised labels in scribbled form.
- Gro.: whether providing corresponding category annotation within group images for Collaborative Camouflaged Object Detection (CoCOD).
- Ref.: whether providing referring images for Referring Camouflaged Object Detection (RefCOD).
- Uns.: whether providing unseen classes for Open-Vocabulary Camouflaged Object Segmentation (OVCOS).
Name | Year | Pub. | Level | Statistics <br />Total | Train | Test | Resolution | Objects | Labels |
---|---|---|---|---|---|---|---|
OVCamo | 2023 | arXiv | I | 11483 | 7713 | 3770 | 300x199~2976x3968 | animals&humans | Cls.(75) Obj. Uns. |
R2C7K | 2023 | arXiv | I | 6615 | - | - | Camo: 300x199~2976x3968<br />Ref: 240x320~9500x9500 | animals&humans<br />N.Cam | Cls.(64) Obj. Ref. |
CoCOD8K | 2023 | TNNLS | I | 8528 | 5933 |2595 | 154x156~5184x3456 | animals&humans | Cls.(70) Obj. Gro. |
CDS2K | 2023 | VI | I | 2492 | 0 |2492 | 322x320~1024x1024 | industrial defect<br />N.Cam. | Cls.(18) B.Box Obj. |
CAM-LDR | 2023 | TCSVT | I | 6066 | 4040 |2026 | 155x155~7360x4912 | animals&humans | Fix. Obj. Ins. Ran. |
S-COD | 2023 | AAAI | I | 4040 | 4040 | 0 | 155x155~7360x4912 | animals&humans | Scr. |
COD10K | 2022 | TPAMI | I | 10000 | 6000 | 4000 | 300x199~2976x3968 | animals&humans<br />N.Cam | Cls.(78) B.Box Obj. Ins. |
CAMO++ | 2022 | TIP | I | 5500 | 3500 | 2000 | unreleased | animals&humans<br />N.Cam | Cls.(93) B.Box Obj. Ins. |
MoCA-Mask | 2022 | CVPR | V | 22939 | 19313 | 3626 | 480x360~1920x1080 | animals | Cls.(44) B.Box Obj. |
CAM-FR | 2021 | CVPR | I | 2280 | 2000 | 280 | 155x155~7360x4912 | animals&humans | Fix. Obj. Ins. Ran. |
NC4K | 2021 | CVPR | I | 4121 | 0 | 4121 | 354x268~1280x960 | animals | Obj. Ins. |
MoCA | 2020 | ACCV | V | 37250 | 0 | 37250 | 480x360~1920x1080 | animals | Cls.(67) B.Box |
CAMO-COCO | 2019 | CVIU | I | 2500 | 2000 | 500 | 154x156~7360x4912 | animals&humans<br />N.Cam. | Obj. |
CPD1K | 2018 | SPL | I | 1000 | 0 | 1000 | 854x480 | people | Obj. |
CHAMELEON | 2017 | - | I | 76 | 0 | 76 | 450x300~2304x3456 | animals | Obj. |
CAD2016 | 2016 | ECCV | V | 836 | 0 | 836 | 640x360 | animals | Cls.(6) Obj. |
<span id = "2-transparent-object-segmentationtos-1">2. Transparent Object Segmentation(TOS)</span>
Name | Year | Pub. | Links | level |
---|---|---|---|---|
ClearPose | 2022 | ECCV | Paper | Image |
Trans10K-v2 | 2021 | IJCAI | Paper | Image |
GDD | 2020 | CVPR | Paper | Image |
Trans10K | 2020 | ECCV | Paper | Image |
TOM-Net | 2018 | CVPR | Paper | Image |
TransCut | 2015 | ICCV | Paper | Image |
<span id = "3-surface-defect-detectionsdd-1">3. Surface Defect Detection(SDD)</span>
Name | Year | Pub. | Links | level |
---|---|---|---|---|
MVTecAD | 2021 | IJCV | Paper | Image |
NEU <br />(spot defect) | 2021 | TIM | Paper | Image |
MagneticTile defect | 2020 | VC | Paper | Image |
KolektorSDD | 2019 | CVPR | Paper | Image |
NEU <br />(steel pit defect) | 2019 | TIM | Paper | Image |
CrackForest | 2016 | TITS | Paper | Image |
NEU<br /> (oil pollution defect) | 2014 | ISIJ | Paper | Image |
DAGM | - | - | Webpage | Image |
<span id = "4-polyp-segmentationps-1">4. Polyp Segmentation(PS)</span>
Name | Year | Pub. | Links | level |
---|---|---|---|---|
LDPolypVideo | 2021 | MICCAI | Paper | Video |
Kvasir-SEG | 2020 | MMM | Paper | Image |
EndoScene | 2017 | J HEALTHC ENG | Paper | Image |
CVC-ColonDB | 2016 | IEEE TMI | Paper | Image |
CVC-ClinicDB | 2015 | CMIG | Paper | Image |
ETIS | 2013 | Int J Comput Assist Radiol Surg | Paper | Image |
ASU-Mayo | - | - | Webpage | Image |
<span id = "5-lung-nodule-detectionlnd-1">5. Lung Nodule Detection(LND)</span>
Name | Year | Pub. | Links | level |
---|---|---|---|---|
PN9 | 2021 | TPAMI | Paper | Image |
<span id = "related-surveys-recommended">Related Surveys Recommended</span>
A Survey of Camouflaged Object Detection and Beyond COD
<br/>arxiv 2024. [Paper] [Code]<br/>Aug. 2024
Advances in deep concealed scene understanding COD
CDS2K dataset
<br/>VI 2023. [Paper] [Code]<br/>Aug. 2023
A systematic review of image-level camouflaged object detection with deep learning COD
<br/>Neucom 2024. [Paper]<br/>Jan. 2024
Rethinking Camouflaged Object Detection: Models and Datasets COD
<br/>
TCSVT 2021. [Paper]<br/>Nov. 2021
Advancements in Optimization Algorithms for Lung Nodule Detection and Classification: A Review LND
<br/>ICOTL 2023. [Paper]<br/>Dec. 2023
Detection of Lung Nodules using Convolution Neural Network: A Review LND
<br/>ICIRCA 2020. [Paper]<br/>Jul. 2020