31 citations · 31 across the 2 of their papers we have counts for
2 papers
cs.CV2023
Asymmetric Patch Sampling for Contrastive Learning
Chengchao Shen, Jianzhong Chen, Shu Wang +3
Asymmetric appearance between positive pair effectively reduces the risk of representation degradation in contrastive learning. However, there are still a mass of appearance simila…
cs.AI2021★ 31 cited
Contrastive Model Inversion for Data-Free Knowledge Distillation
Gongfan Fang, Jie Song, Xinchao Wang +3
Model inversion, whose goal is to recover training data from a pre-trained model, has been recently proved feasible. However, existing inversion methods usually suffer from the mod…