RT-DETR family algorithms implemented based on MMDetection, including RT-DETR, RT-DETRv2, RT-DETRv4, DFINE, DEIM and DEIMv2.
Python
66
2,797 commits
updated Feb 1, 2026
| DEIM v2 | ours | official | gap | checked | log |
|---|---|---|---|---|---|
| deimv2_dinov3_m_8xb4-102e_coco | 53.1 | 53.0 | +0.1 | ✅ | download |
| deimv2_dinov3_l_8xb4-68e_coco | 56.0 | 56.0 | +0.0 | ✅ | download |
| deimv2_dinov3_x_8xb4-58e_coco | 57.8 | 57.8 | +0.0 | ✅ | download |
| DEIM | ours | official | gap | checked | log |
|---|---|---|---|---|---|
| deim_hgnetv2_n_8xb16-160e_coco | 42.9 | 43.0 | -0.1 | ✅ | download |
| deim_r18vd_8xb2-120e_coco | 49.2 | 49.0 | +0.2 | ✅ | download |
| D-FINE | ours | official | gap | checked | log |
|---|---|---|---|---|---|
| dfine_hgnetv2_n_8xb16-160e_coco | 42.6 | 42.8 | -0.2 | download |
| RT-DETR v2 | ours | official | gap | checked | log |
|---|---|---|---|---|---|
| rtdetrv2_r18vd_8xb2-120e_coco | 48.3 | 48.1 | +0.2 | ✅ | download |
| rtdetrv2_r34vd_dsp_8xb2-12e_coco | 49.3 | 49.1 | +0.2 | ✅ | download |
| RT-DETR | ours | official | gap | checked | log |
|---|---|---|---|---|---|
| rtdetr_r18vd_8xb2-72e_coco | 46.7 | 46.5 | +0.2 | ✅ | download |
| rtdetr_r50vd_8xb2-72e_coco | 53.1 | 53.1 | +0.0 | ✅ | download |
DETRs Beat YOLOs on Real-time Object Detection [RT-DETR] [CVPR 2024]
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@misc{lv2023detrs,
title={DETRs Beat YOLOs on Real-time Object Detection},
author={Yian Zhao and Wenyu Lv and Shangliang Xu and Jinman Wei and Guanzhong Wang and Qingqing Dang and Yi Liu and Jie Chen},
year={2023},
eprint={2304.08069},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer
Wenyu Lv, Yian Zhao, Qinyao Chang, Kui Huang, Guanzhong Wang, Yi Liu
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![]()
@misc{lv2024rtdetrv2improvedbaselinebagoffreebies,
title={RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer},
author={Wenyu Lv and Yian Zhao and Qinyao Chang and Kui Huang and Guanzhong Wang and Yi Liu},
year={2024},
eprint={2407.17140},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2407.17140},
}
D-FINE: Redefine Regression Task of DETRs as Fine-grained Distribution Refinement [ICLR 2025 Spotlight]
Yansong Peng, Hebei Li, Peixi Wu, Yueyi Zhang, Xiaoyan Sun, Feng Wu
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@misc{peng2024dfine,
title={D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement},
author={Yansong Peng and Hebei Li and Peixi Wu and Yueyi Zhang and Xiaoyan Sun and Feng Wu},
year={2024},
eprint={2410.13842},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
DEIM: DETR with Improved Matching for Fast Convergence [CVPR 2025]
Shihua Huang, Zhichao Lu, Xiaodong Cun, Yongjun Yu, Xiao Zhou, Xi Shen
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@misc{huang2024deim,
title={DEIM: DETR with Improved Matching for Fast Convergence},
author={Shihua, Huang and Zhichao, Lu and Xiaodong, Cun and Yongjun, Yu and Xiao, Zhou and Xi, Shen},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year={2025},
}
Real-Time Object Detection Meets DINOv3 [DEIMv2]
Shihua Huang, Yongjie Hou, Longfei Liu, Xuanlong Yu, Xi Shen
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@article{huang2025deimv2,
title={Real-Time Object Detection Meets DINOv3},
author={Huang, Shihua and Hou, Yongjie and Liu, Longfei and Yu, Xuanlong and Shen, Xi},
journal={arXiv},
year={2025}
}
RT-DETRv4: Painlessly Furthering Real-Time Object Detection with Vision Foundation Models
Zijun Liao* , Yian Zhao* , Xin Shan, Yu Yan, Chang Liu, Lei Lu, Xiangyang Ji, Jie Chen
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![]()
@article{liao2025rtdetrv4,
title={RT-DETRv4: Painlessly Furthering Real-Time Object Detection with Vision Foundation Models},
author={Zijun Liao and Yian Zhao and Xin Shan and Yu Yan and Chang Liu and Lei Lu and Xiangyang Ji and Jie Chen},
journal={arXiv preprint arXiv:2510.25257},
year={2025}
}
RT-DETR family algorithms implemented based on MMDetection, including RT-DETR, RT-DETRv2, RT-DETRv4, DFINE, DEIM and DEIMv2.
Python
66
2,797 commits
updated Feb 1, 2026
| DEIM v2 | ours | official | gap | checked | log |
|---|---|---|---|---|---|
| deimv2_dinov3_m_8xb4-102e_coco | 53.1 | 53.0 | +0.1 | ✅ | download |
| deimv2_dinov3_l_8xb4-68e_coco | 56.0 | 56.0 | +0.0 | ✅ | download |
| deimv2_dinov3_x_8xb4-58e_coco | 57.8 | 57.8 | +0.0 | ✅ | download |
| DEIM | ours | official | gap | checked | log |
|---|---|---|---|---|---|
| deim_hgnetv2_n_8xb16-160e_coco | 42.9 | 43.0 | -0.1 | ✅ | download |
| deim_r18vd_8xb2-120e_coco | 49.2 | 49.0 | +0.2 | ✅ | download |
| D-FINE | ours | official | gap | checked | log |
|---|---|---|---|---|---|
| dfine_hgnetv2_n_8xb16-160e_coco | 42.6 | 42.8 | -0.2 | download |
| RT-DETR v2 | ours | official | gap | checked | log |
|---|---|---|---|---|---|
| rtdetrv2_r18vd_8xb2-120e_coco | 48.3 | 48.1 | +0.2 | ✅ | download |
| rtdetrv2_r34vd_dsp_8xb2-12e_coco | 49.3 | 49.1 | +0.2 | ✅ | download |
| RT-DETR | ours | official | gap | checked | log |
|---|---|---|---|---|---|
| rtdetr_r18vd_8xb2-72e_coco | 46.7 | 46.5 | +0.2 | ✅ | download |
| rtdetr_r50vd_8xb2-72e_coco | 53.1 | 53.1 | +0.0 | ✅ | download |
DETRs Beat YOLOs on Real-time Object Detection [RT-DETR] [CVPR 2024]
![]()
![]()
@misc{lv2023detrs,
title={DETRs Beat YOLOs on Real-time Object Detection},
author={Yian Zhao and Wenyu Lv and Shangliang Xu and Jinman Wei and Guanzhong Wang and Qingqing Dang and Yi Liu and Jie Chen},
year={2023},
eprint={2304.08069},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer
Wenyu Lv, Yian Zhao, Qinyao Chang, Kui Huang, Guanzhong Wang, Yi Liu
![]()
![]()
@misc{lv2024rtdetrv2improvedbaselinebagoffreebies,
title={RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer},
author={Wenyu Lv and Yian Zhao and Qinyao Chang and Kui Huang and Guanzhong Wang and Yi Liu},
year={2024},
eprint={2407.17140},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2407.17140},
}
D-FINE: Redefine Regression Task of DETRs as Fine-grained Distribution Refinement [ICLR 2025 Spotlight]
Yansong Peng, Hebei Li, Peixi Wu, Yueyi Zhang, Xiaoyan Sun, Feng Wu
![]()
![]()
@misc{peng2024dfine,
title={D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement},
author={Yansong Peng and Hebei Li and Peixi Wu and Yueyi Zhang and Xiaoyan Sun and Feng Wu},
year={2024},
eprint={2410.13842},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
DEIM: DETR with Improved Matching for Fast Convergence [CVPR 2025]
Shihua Huang, Zhichao Lu, Xiaodong Cun, Yongjun Yu, Xiao Zhou, Xi Shen
![]()
![]()
@misc{huang2024deim,
title={DEIM: DETR with Improved Matching for Fast Convergence},
author={Shihua, Huang and Zhichao, Lu and Xiaodong, Cun and Yongjun, Yu and Xiao, Zhou and Xi, Shen},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year={2025},
}
Real-Time Object Detection Meets DINOv3 [DEIMv2]
Shihua Huang, Yongjie Hou, Longfei Liu, Xuanlong Yu, Xi Shen
![]()
![]()
@article{huang2025deimv2,
title={Real-Time Object Detection Meets DINOv3},
author={Huang, Shihua and Hou, Yongjie and Liu, Longfei and Yu, Xuanlong and Shen, Xi},
journal={arXiv},
year={2025}
}
RT-DETRv4: Painlessly Furthering Real-Time Object Detection with Vision Foundation Models
Zijun Liao* , Yian Zhao* , Xin Shan, Yu Yan, Chang Liu, Lei Lu, Xiangyang Ji, Jie Chen
![]()
![]()
@article{liao2025rtdetrv4,
title={RT-DETRv4: Painlessly Furthering Real-Time Object Detection with Vision Foundation Models},
author={Zijun Liao and Yian Zhao and Xin Shan and Yu Yan and Chang Liu and Lei Lu and Xiangyang Ji and Jie Chen},
journal={arXiv preprint arXiv:2510.25257},
year={2025}
}