---
license: other
license_name: adelaidet-noncommercial
license_link: LICENSE
tags:
  - scene-text-detection
  - detection-transformer
  - pytorch
---

# DPText-DETR (mirror)

This repository is an **archival mirror of pretrained weights** from the official
[DPText-DETR](https://github.com/ymy-k/DPText-DETR) repository. No changes have been
made to the weights themselves; they are re-hosted here for long-term preservation
as part of a personal project.

- **Original paper:** Ye, M., Zhang, J., Zhao, S., Liu, J., Du, B., & Tao, D. (2023).
  *DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer.*
  AAAI 2023 (Oral).
- **Original code:** https://github.com/ymy-k/DPText-DETR
- **Checkpoint in this repo:** `art_final.pth` - the fine-tuned model for the
  ICDAR19 ArT benchmark, as released by the original authors.
- **All credit** for the model architecture, training, and weights belongs to the
  original authors. This repo makes no claim of authorship over the model.

## License

These weights are distributed under the original **AdelaiDet non-commercial license**
(see the LICENSE file in this repo). In short:

- Free to use, copy, and redistribute for **non-commercial / research purposes**,
  provided the copyright notice and disclaimer are retained.
- **Commercial use is not permitted** under this license. For a commercial license,
  contact the original AdelaiDet authors (chhshen@gmail.com), as noted in the LICENSE file.

This mirror does not alter or override those terms.

## Citation

If you use this model, please cite the original paper:

```bibtex
@inproceedings{ye2022dptext,
  title={DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer},
  author={Ye, Maoyuan and Zhang, Jing and Zhao, Shanshan and Liu, Juhua and Du, Bo and Tao, Dacheng},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={37},
  number={3},
  pages={3241--3249},
  year={2023}
}
```