Channel Reassessment Attention Module

Approach

The architecture of CRA module.

model	top-1 error	top-5 error	FLOPs	params
ResNet-50	24.20	7.15	4.11G	25.56M
CRA-ResNet-50	22.77	6.47	4.11G	26.31M
ResNet-101	23.12	6.67	7.84G	44.55M
CRA-ResNet-101	21.60	5.93	7.84G	46.17M
ResNeXt-101	21.27	5.79	8.01G	44.18M
CRA-ResNeXt-101	20.71	5.47	8.02G	45.80M

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
configs		configs
img		img
loaders		loaders
losses		losses
models		models
optimizers		optimizers
runs/cra_imagenet/1		runs/cra_imagenet/1
schedulers		schedulers
README.md		README.md
metrics.py		metrics.py
test.py		test.py
train.py		train.py
utils.py		utils.py
validate.py		validate.py