Awesome
MoLF-NeurIPS19
Code repository for our paper entilted "Memory-oriented Decoder for Light Field Salient Object Detection".
- [Code] You can found in this link and the code is t551. Moreover, the checkpoint is here and the code is tjqy.
- [poster] A brief explanation for paper
- [Dataset] Our light field saliency datset(DUTLF-FS) is part of DUTLF. Our DUTLF-FS mainly rely on focal stacks in light field.
- [DUTLF-V2] DUTLF-V2 is the updated version of DUTLF-V1, which consists of 4204 light field samples. We are working on it and will make it publicly available soon.
Datasets
- Dataset: DUTLF
- This dataset consists of DUTLF-MV, DUTLF-FS, DUTLF-Depth.
- The dataset will be expanded to 3000 about real scenes.
- We are working on it and will make it publicly available soon.
- Dataset: DUTLF-FS
- DUTLF-FS is part of DUTLF dataset captured by Lytro camera, yet our dataset mainly rely on focal stack in light field for accurate salient object detection.
- A large scale light field saliency dataset(DUTLF-FS) with 1465 paired images contains focal stack and RGB images. In addition, the dataset download link is here and the fetch code is vecy.
- Three problematic images were deleted for better use in DUTLF-FS, and a detail description can be found in dataset download files.
Results
| DUTLF-FS | | LFSD | | HFUT |
- Note: Several samples can't synthesize 12 focal slices on LFSD, and so LFSD only contains 93 samples.
Citation
@inproceedings{Zhang_2019_MoLF,
title={Memory-oriented Decoder for Light Field Salient Object Detection},
author={Zhang, Miao and Li, Jingjing and Ji, Wei and Piao, Yongri and Lu, Huchuan},
booktitle={Advances in Neural Information Processing Systems},
pages={896--906},
year={2019}
}
Contact Us
If you have any questions, please contact us ( weiji.dlut@gmail.com ).