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https://github.com/vitae-transformer/deepsolo
The official repo for [CVPR'23] "DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting" & [ArXiv'23] "DeepSolo++: Let Transformer Decoder with Explicit Points Solo for Multilingual Text Spotting"
https://github.com/vitae-transformer/deepsolo
chinese-text-spotting detection-transformer explicit-point-query multilingual-text-spotting scene-text-spotting
Last synced: 3 days ago
JSON representation
The official repo for [CVPR'23] "DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting" & [ArXiv'23] "DeepSolo++: Let Transformer Decoder with Explicit Points Solo for Multilingual Text Spotting"
- Host: GitHub
- URL: https://github.com/vitae-transformer/deepsolo
- Owner: ViTAE-Transformer
- License: other
- Created: 2022-11-23T07:20:33.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-09T03:20:10.000Z (6 months ago)
- Last Synced: 2025-01-22T14:02:51.497Z (10 days ago)
- Topics: chinese-text-spotting, detection-transformer, explicit-point-query, multilingual-text-spotting, scene-text-spotting
- Language: Python
- Homepage:
- Size: 16.3 MB
- Stars: 255
- Watchers: 7
- Forks: 35
- Open Issues: 31
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
DeepSolo & DeepSolo++
News |
Usage |
Citation |
Acknowledgement
This is the official repo for the papers:
> [**DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting**](https://arxiv.org/abs/2211.10772)
>
> [**DeepSolo++: Let Transformer Decoder with Explicit Points Solo for Multilingual Text Spotting**](https://arxiv.org/abs/2305.19957)
## 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** ](https://arxiv.org/abs/2401.17904) | [Code](https://github.com/ymy-k/Hi-SAM)
>
> :sparkles: [**GoMatching: A Simple Baseline for Video Text Spotting via Long and Short Term Matching** ](https://arxiv.org/abs/2401.07080) | [Code](https://github.com/Hxyz-123/GoMatching)
>
> [**DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer** ](https://arxiv.org/abs/2207.04491) | [Code](https://github.com/ymy-k/DPText-DETR)
Other applications of [ViTAE](https://github.com/ViTAE-Transformer/ViTAE-Transformer) inlcude: [ViTPose](https://github.com/ViTAE-Transformer/ViTPose) | [Remote Sensing](https://github.com/ViTAE-Transformer/ViTAE-Transformer-Remote-Sensing) | [Matting](https://github.com/ViTAE-Transformer/ViTAE-Transformer-Matting) | [VSA](https://github.com/ViTAE-Transformer/ViTAE-VSA) | [Video Object Segmentation](https://github.com/ViTAE-Transformer/VOS-LLB)
## Usage
See README for [DeepSolo](./DeepSolo/README.md) and [DeepSolo++](./DeepSolo++/README.md)
## Citation
If you find DeepSolo helpful, please consider giving this repo a star :star: and citing:
```bibtex
@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](https://github.com/aim-uofa/AdelaiDet). For academic use, this project is licensed under the 2-clause BSD License.