News | Usage | Citation | Acknowledgement

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

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

• [2025/05/16]: 🚀🚀 We release LogicOCR, a benchmark designed to evaluate the logical reasoning abilities of Large Multimodal Models (LMMs) on text-rich images, while minimizing reliance on domain-specific knowledge. We offer key insights for enhancing multimodal reasoning.

• [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. 🎉🎉

Relevant Project:

✨ LogicOCR: Do Your Large Multimodal Models Excel at Logical Reasoning on Text-Rich Images? | Project Page

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

✨ 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

See README for DeepSolo and DeepSolo++

If you find DeepSolo helpful, please consider giving this repo a 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}
}

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