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ShoufaChen

DiffusionDet

[ICCV2023 Best Paper Finalist] PyTorch implementation of DiffusionDet (https://arxiv.org/abs/2211.09788).

Model DevelopmentArchitecturePython
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Created 2022-11-17 · Updated 2026-10-13 · #8805 today
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ShoufaChen

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Key parameters and specifications
Key parameters and specifications
ParameterValue
LanguagePython
CategoryModel Development
SubcategoryArchitecture
KeywordsDiffusion, Object detection
Stars2,259
Forks186
Contributors1
Created date2022-11-17
Updated date2026-10-13
Stars in 1 day0
Stars in 7 days0
Rank8,805
Previous rank8,867
Rank change62
7-day stars rank12,092
Previous 7-day stars rank12,150
7-day stars rank change58
Total stars rank5,751
Previous total stars rank5,746
Total stars rank change-5
CountryHong Kong
README summary

DiffusionDet: Diffusion Model for Object Detection **DiffusionDet is the first work of diffusion model for object detection. ** **DiffusionDet: Diffusion Model for Object Detection** Shoufa Chen, Peize Sun, Yibing Song, Ping Luo *arXiv 2211. 09788* Updates (11/2022) Code is released. 9 | model Getting Started The installation instruction and usage are in Getting Started with DiffusionDet. License This project is under the CC-BY-NC 4. Citing DiffusionDet If you use DiffusionDet in your research or wish to refer to the

baseline results published here, please use the following BibTeX entry.

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ShoufaChen/DiffusionDet has 2,259 stars and 186 forks.

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ShoufaChen/DiffusionDet is ranked 8,805.

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ShoufaChen/DiffusionDet has 2,259 stars, uses Python and belongs to Model Development.

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ShoufaChen/DiffusionDet is compared with TuringLang/Turing.jl, ranked 8,804 with 2,260 stars.

README

DiffusionDet: Diffusion Model for Object Detection

DiffusionDet is the first work of diffusion model for object detection.

DiffusionDet: Diffusion Model for Object Detection
Shoufa Chen, Peize Sun, Yibing Song, Ping Luo
arXiv 2211.09788

Updates

  • (11/2022) Code is released.

Models

Method Box AP (1 step) Box AP (4 step) Download
COCO-Res50 45.5 46.1 model
COCO-Res101 46.6 46.9 model
COCO-SwinBase 52.3 52.7 model
LVIS-Res50 30.4 31.8 model
LVIS-Res101 31.9 32.9 model
LVIS-SwinBase 40.6 41.9 model

Getting Started

The installation instruction and usage are in Getting Started with DiffusionDet.

License

This project is under the CC-BY-NC 4.0 license. See LICENSE for details.

Citing DiffusionDet

If you use DiffusionDet in your research or wish to refer to the baseline results published here, please use the following BibTeX entry.

@article{chen2022diffusiondet,
      title={DiffusionDet: Diffusion Model for Object Detection},
      author={Chen, Shoufa and Sun, Peize and Song, Yibing and Luo, Ping},
      journal={arXiv preprint arXiv:2211.09788},
      year={2022}
}
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