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Grassmann Class Representation

Official code for "Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation (ICCV 2023)"

https://github.com/innerlee/gcr/assets/9464825/37708eb8-740c-46df-ad24-7bcf6ef592c9

Grassmann class representation

Installation

Run

python setup.py develop

Requirements

pytorch >= 1.13
mmpretrain

Prepare data

Put ImageNet1-K dataset on data/imagenet folder

ImageNet1-K Pretrained Weights

Architecture	Trick	Class Representation	Dim	Top1	Top5	Config	Log	Checkpoint
ResNet50-D		Vector	-	78.05	93.90	config	log	ckpt
ResNet50-D		GCR	1	78.42	94.14	config	log	ckpt
ResNet50-D		GCR	4	78.68	94.32	config	log	ckpt
ResNet50-D		GCR	8	79.26	94.44	config	log	ckpt
ResNet50-D		GCR	16	79.21	94.37	config	log	ckpt
ResNet50-D		GCR	32	78.63	94.05	config	log	ckpt
ResNet50-D	RSB-A1	Vector	-	80.53	94.98	config	log	ckpt
ResNet50-D	RSB-A1	GCR	8	81.00	95.40	config	log	ckpt
ResNet50-D	RSB-A1 FixRes	GCR	8	81.30	95.42	config	log	ckpt
ResNet50-D	RSB-A2	Vector	-	80.29	94.86	config	log	ckpt
ResNet50-D	RSB-A2	GCR	8	80.75	95.24	config	log	ckpt
ResNet50-D	RSB-A2 FixRes	GCR	8	81.04	95.46	config	log	ckpt
ResNet50-D	RSB-A3	Vector	-	79.36	94.47	config	log	ckpt
ResNet50-D	RSB-A3	GCR	8	79.64	94.85	config	log	ckpt
ResNet50-D	RSB-A3 FixRes	GCR	8	80.20	95.15	config	log	ckpt
ResNet101-D		Vector	-	79.31	94.67	config	log	ckpt
ResNet101-D		GCR	8	80.24	94.95	config	log	ckpt
ResNet152-D		Vector	-	80.00	95.02	config	log	ckpt
ResNet152-D		GCR	8	80.44	95.21	config	log	ckpt
VGG13-BN		Vector	-	72.02	90.79	config	log	ckpt
VGG13-BN		GCR	8	73.40	91.30	config	log	ckpt
Swin-T		Vector	-	81.06	95.51	config	log	ckpt
Swin-T		GCR	8	81.63	95.77	config	log	ckpt
Deit3-S		Vector	-	81.53	95.22	config	log	ckpt
Deit3-S		GCR	8	82.18	95.73	config	log	ckpt

Training

# train ResNet50d baseline with 8 gpus
./tools/dist_train.sh configs/resnet/resnet50d_8xb32-coslr_in1k.py 8

# train the gcr version
./tools/dist_train.sh configs/resnet/resnet50d_8xb32-coslr_in1k_gcr8.py 8

Citation

@inproceedings{haoqi2023gcr,
title = {Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation},
author = {Wang, Haoqi and Li, Zhizhong and Zhang, Wayne},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
year = {2023}
}

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