• Corpus ID: 233324262

PP-YOLOv2: A Practical Object Detector

@article{Huang2021PPYOLOv2AP,
  title={PP-YOLOv2: A Practical Object Detector},
  author={Xin Huang and Xinxin Wang and Wenyu Lv and Xiaying Bai and Xiang Long and Kaipeng Deng and Qingqing Dang and Shumin Han and Qiwen Liu and Xiaoguang Hu and Dianhai Yu and Yanjun Ma and Osamu Yoshie},
  journal={ArXiv},
  year={2021},
  volume={abs/2104.10419}
}
Being effective and efficient is essential to an object detector for practical use. To meet these two concerns, we comprehensively evaluate a collection of existing refinements to improve the performance of PP-YOLO while almost keep the infer time unchanged. This paper will analyze a collection of refinements and empirically evaluate their impact on the final model performance through incremental ablation study. Things we tried that didn’t work will also be discussed. By combining multiple… 

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