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DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting

DeepSolo++: Let Transformer Decoder with Explicit Points Solo for Multilingual Text Spotting

News

2024.04.25 Update DeepSolo models finetuned on BOVText and DSText video datasets.

2023.06.02 Update the pre-trained and fine-tuned Chinese scene text spotting model (78.3% 1-NED on ICDAR 2019 ReCTS).

2023.05.31 The extension paper (DeepSolo++) is submitted to ArXiv. The code and models will be released soon.

2023.02.28 DeepSolo is accepted by CVPR 2023. :tada::tada:

Relevant Project:

:sparkles: Hi-SAM: Marrying Segment Anything Model for Hierarchical Text Segmentation | Code

:sparkles: GoMatching: A Simple Baseline for Video Text Spotting via Long and Short Term Matching | Code

DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer | Code

Other applications of ViTAE inlcude: ViTPose | Remote Sensing | Matting | VSA | Video Object Segmentation

Usage

See README for DeepSolo and DeepSolo++

Citation

If you find DeepSolo helpful, please consider giving this repo a star :star: and citing:

@inproceedings{ye2023deepsolo,
  title={DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting},
  author={Ye, Maoyuan and Zhang, Jing and Zhao, Shanshan and Liu, Juhua and Liu, Tongliang and Du, Bo and Tao, Dacheng},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={19348--19357},
  year={2023}
}

@article{ye2023deepsolo++,
  title={DeepSolo++: Let Transformer Decoder with Explicit Points Solo for Multilingual Text Spotting},
  author={Ye, Maoyuan and Zhang, Jing and Zhao, Shanshan and Liu, Juhua and Liu, Tongliang and Du, Bo and Tao, Dacheng},
  booktitle={arxiv preprint arXiv:2305.19957},
  year={2023}
}

Acknowledgement

This project is based on Adelaidet. For academic use, this project is licensed under the 2-clause BSD License.