yangjun dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829		1 rok pred
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README.md	dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829	1 rok pred
ppyoloe_convnext_tiny_36e_coco.yml	dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829	1 rok pred
yolox_convnext_s_36e_coco.yml	dfa27afb39 提交PaddleDetection develop 分支 d56cf3f7c294a7138013dac21f87da4ea6bee829	1 rok pred

ConvNeXt (A ConvNet for the 2020s)

模型库

ConvNeXt on COCO

Citations

@Article{liu2022convnet,
  author  = {Zhuang Liu and Hanzi Mao and Chao-Yuan Wu and Christoph Feichtenhofer and Trevor Darrell and Saining Xie},
  title   = {A ConvNet for the 2020s},
  journal = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year    = {2022},
}

网络网络	输入尺寸	图片数/GPU	学习率策略	mAP^val 0.5:0.95	mAP^val 0.5	Params(M)	FLOPs(G)	下载链接	配置文件
PP-YOLOE-ConvNeXt-tiny	640	16	36e	44.6	63.3	33.04	13.87	下载链接	配置文件
YOLOX-ConvNeXt-s	640	8	36e	44.6	65.3	36.20	27.52	下载链接	配置文件

README.md

ConvNeXt (A ConvNet for the 2020s)

模型库

ConvNeXt on COCO

Citations