convnext

Introduction

Official Repo

Code Snippet

ConvNeXt (CVPR'2022)

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

Results

ADE20k

Segmentor	Pretrain	Backbone	Crop Size	Schedule	Train/Eval Set	mIoU	Download
UperNet	ImageNet-1k-224x224	ConvNeXt-T	512x512	LR/POLICY/BS/EPOCH: 0.0001/poly/16/130	train/val	46.25%	cfg | model | log
UperNet	ImageNet-1k-224x224	ConvNeXt-S	512x512	LR/POLICY/BS/EPOCH: 0.0001/poly/16/130	train/val	48.68%	cfg | model | log
UperNet	ImageNet-1k-224x224	ConvNeXt-B	512x512	LR/POLICY/BS/EPOCH: 0.0001/poly/16/130	train/val	48.97%	cfg | model | log
UperNet	ImageNet-21k-224x224	ConvNeXt-B-21k	640x640	LR/POLICY/BS/EPOCH: 0.0001/poly/16/130	train/val	52.71%	cfg | model | log
UperNet	ImageNet-21k-224x224	ConvNeXt-L-21k	640x640	LR/POLICY/BS/EPOCH: 0.0001/poly/16/130	train/val	53.41%	cfg | model | log
UperNet	ImageNet-21k-224x224	ConvNeXt-XL-21k	640x640	LR/POLICY/BS/EPOCH: 0.0001/poly/16/130	train/val	53.68%	cfg | model | log

More

You can also download the model weights from following sources:

• BaiduNetdisk: https://pan.baidu.com/s/1gD-NJJWOtaHCtB0qHE79rA with access code s757