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The RT-DETRv2 model was proposed in [RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer](https://arxiv.org/abs/2407.17140) by Wenyu Lv, Yian Zhao, Qinyao Chang, Kui Huang, Guanzhong Wang, Yi Liu. RT-DETRv2 refines RT-DETR by introducing selective multi-scale feature extraction, a discrete sampling operator for broader deployment compatibility, and improved training strategies like dynamic data augmentation and scale-adaptive hyperparameters.
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These changes enhance flexibility and practicality while maintaining real-time performance.
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This model was contributed by
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### **Performance**
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The RT-DETRv2 model was proposed in [RT-DETRv2: Improved Baseline with Bag-of-Freebies for Real-Time Detection Transformer](https://arxiv.org/abs/2407.17140) by Wenyu Lv, Yian Zhao, Qinyao Chang, Kui Huang, Guanzhong Wang, Yi Liu. RT-DETRv2 refines RT-DETR by introducing selective multi-scale feature extraction, a discrete sampling operator for broader deployment compatibility, and improved training strategies like dynamic data augmentation and scale-adaptive hyperparameters.
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These changes enhance flexibility and practicality while maintaining real-time performance.
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This model was contributed by [@jadechoghari](https://x.com/jadechoghari) with the help of [@cyrilvallez](https://huggingface.co/cyrilvallez) and [@qubvel-hf](https://huggingface.co/qubvel-hf)
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### **Performance**
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