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* update readme

* update changelog

* update

* add citation

* add citation
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rentainhe authored Jul 16, 2023
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13 changes: 5 additions & 8 deletions README.md
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Expand Up @@ -78,14 +78,9 @@ The repo name detrex has several interpretations:
- <font color=#008000> <b> de-t.rex </b> </font>: de means 'the' in Dutch. T.rex, also called Tyrannosaurus Rex, means 'king of the tyrant lizards' and connects to our research work 'DINO', which is short for Dinosaur.

## What's New
v0.4.0 was released on 02/06/2023:
- Support [CO-MOT](./projects/co_mot/) aims for End-to-End Multi-Object Tracking by [Feng Yan](https://scholar.google.com/citations?user=gO4divAAAAAJ&hl=zh-CN&oi=sra).
- Release `DINO` with optimized hyper-parameters which achieves `50.0 AP` under 1x settings.
- Release pretrained DINO based on `InternImage`, `ConvNeXt-1K pretrained` backbones.
- Release `Deformable-DETR-R50` pretrained weights.
- Release `DETA` and better `H-DETR` pretrained weights: achieving `50.2 AP` and `49.1 AP` respectively.


v0.5.0 was released on 16/07/2023:
- Support [SQR-DETR (CVPR 2023)](https://github.com/IDEA-Research/detrex/tree/main/projects/sqr_detr), credits to [Fangyi Chen](https://github.com/Fangyi-Chen)
- Support [EVA-01](https://github.com/baaivision/EVA/tree/master/EVA-01) and [EVA-02](https://github.com/baaivision/EVA/tree/master/EVA-02) backbones, please check [DINO-EVA](./projects/dino_eva/) for more benchmarking results.

Please see [changelog.md](./changlog.md) for details and release history.

Expand Down Expand Up @@ -134,6 +129,8 @@ Results and models are available in [model zoo](https://detrex.readthedocs.io/en
- [x] [MaskDINO (CVPR'2023)](./projects/maskdino/)
- [x] [CO-MOT (ArXiv'2023)](./projects/co_mot/)
- [x] [SQR-DETR (CVPR'2023)](./projects/sqr_detr/)
- [x] [EVA-01 (CVPR'2023 Highlight)](./projects/dino_eva/)
- [x] [EVA-02 (ArXiv'2023)](./projects/dino_eva/)

Please see [projects](./projects/) for the details about projects that are built based on detrex.

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5 changes: 5 additions & 0 deletions changlog.md
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## Change Log

### v0.5.0 (16/07/2023):
- Support [SQR-DETR (CVPR 2023)](https://github.com/IDEA-Research/detrex/tree/main/projects/sqr_detr), credits to [Fangyi Chen](https://github.com/Fangyi-Chen)
- Support [EVA-01](https://github.com/baaivision/EVA/tree/master/EVA-01) and [EVA-02](https://github.com/baaivision/EVA/tree/master/EVA-02) backbones, please check [DINO-EVA](https://github.com/IDEA-Research/detrex/tree/main/projects/dino_eva) for more benchmarking results.


### v0.4.0 (02/06/2023):
- Support [CO-MOT](./projects/co_mot/) aims for End-to-End Multi-Object Tracking by [Feng Yan](https://scholar.google.com/citations?user=gO4divAAAAAJ&hl=zh-CN&oi=sra).
- Release `DINO` with optimized hyper-parameters which achieves `50.0 AP` under 1x settings.
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27 changes: 18 additions & 9 deletions projects/dino_eva/README.md
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Expand Up @@ -78,6 +78,24 @@ python tools/train_net.py --config-file projects/dino_eva/configs/path/to/config
## Citing DINO and EVA
If you find our work helpful for your research, please consider citing the following BibTeX entry.

```BibTex
@article{EVA,
title={EVA: Exploring the Limits of Masked Visual Representation Learning at Scale},
author={Fang, Yuxin and Wang, Wen and Xie, Binhui and Sun, Quan and Wu, Ledell and Wang, Xinggang and Huang, Tiejun and Wang, Xinlong and Cao, Yue},
journal={arXiv preprint arXiv:2211.07636},
year={2022}
}
```

```BibTex
@article{EVA02,
title={EVA-02: A Visual Representation for Neon Genesis},
author={Fang, Yuxin and Sun, Quan and Wang, Xinggang and Huang, Tiejun and Wang, Xinlong and Cao, Yue},
journal={arXiv preprint arXiv:2303.11331},
year={2023}
}
```

```BibTex
@misc{zhang2022dino,
title={DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection},
Expand All @@ -87,13 +105,4 @@ If you find our work helpful for your research, please consider citing the follo
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```

```BibTex
@article{EVA,
title={EVA: Exploring the Limits of Masked Visual Representation Learning at Scale},
author={Fang, Yuxin and Wang, Wen and Xie, Binhui and Sun, Quan and Wu, Ledell and Wang, Xinggang and Huang, Tiejun and Wang, Xinlong and Cao, Yue},
journal={arXiv preprint arXiv:2211.07636},
year={2022}
}
```

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