PyTorch implementation of Res2Net

This repository contains code for Res2Net based on Res2Net: A New Multi-scale Backbone Architecture implemented in PyTorch.

Requirements

• Python 3.6
• PyTorch 1.0

Training

CIFAR-100

• Res2NeXt-29, 6cx24wx4scale:

  python train.py --dataset cifar100 --arch res2next29_6cx24wx4scale

• Res2NeXt-29, 8cx25wx4scale:

  python train.py --dataset cifar100 --arch res2next29_8cx25wx4scale

• Res2NeXt-29, 6cx24wx6scale:

  python train.py --dataset cifar100 --arch res2next29_6cx24wx6scale

• Res2NeXt-29, 6cx24wx4scale-SE:

  python train.py --dataset cifar100 --arch res2next29_6cx24wx4scale_se

• Res2NeXt-29, 8cx25wx4scale-SE:

  python train.py --dataset cifar100 --arch res2next29_8cx25wx4scale_se

• Res2NeXt-29, 6cx24wx6scale-SE:

  python train.py --dataset cifar100 --arch res2next29_6cx24wx6scale_se

ImageNet

• Res2Net-50:

  python train.py --dataset imagenet --imagenet-dir </path/to/data> --arch res2net50 --epoch 100 --milestones 30 --weight-decay 1e-4

• Res2Net-101:

  python train.py --dataset imagenet --imagenet-dir </path/to/data> --arch res2net101 --epoch 100 --milestones 30 --weight-decay 1e-4

• Res2Net-152:

  python train.py --dataset imagenet --imagenet-dir </path/to/data> --arch res2net152 --epoch 100 --milestones 30 --weight-decay 1e-4

• Res2NeXt-50_32x4d:

  python train.py --dataset imagenet --imagenet-dir </path/to/data> --arch res2next50_32x4d --epoch 100 --milestones 30 --weight-decay 1e-4

• SE-Res2Net-50:

  python train.py --dataset imagenet --imagenet-dir </path/to/data> --arch se_res2net50 --epoch 100 --milestones 30 --weight-decay 1e-4

Results

Coming soon...