| --- |
| 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} |
| } |
| ``` |
