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20192022
most citedGenerative Domain Adaptation for Face Anti-Spoofing

67 citations · 138 across the 14 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.CV2021★ 1 cited

Reciprocal Normalization for Domain Adaptation

Zhiyong Huang, Kekai Sheng, Ke Li +5

Batch normalization (BN) is widely used in modern deep neural networks, which has been shown to represent the domain-related knowledge, and thus is ineffective for cross-domain tas…

cs.CV2021★ 15 cited

Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer

Yifan Xu, Zhijie Zhang, Mengdan Zhang +6

Vision transformers (ViTs) have recently received explosive popularity, but the huge computational cost is still a severe issue. Since the computation complexity of ViT is quadrati…

cs.CV2021★ 6 cited

Dual Reweighting Domain Generalization for Face Presentation Attack Detection

Shubao Liu, Ke-Yue Zhang, Taiping Yao +6

Face anti-spoofing approaches based on domain generalization (DG) have drawn growing attention due to their robustness for unseen scenarios. Previous methods treat each sample from…

cs.CV2021★ 2 cited

Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing

Zhihong Chen, Taiping Yao, Kekai Sheng +5

Face anti-spoofing approach based on domain generalization(DG) has drawn growing attention due to its robustness forunseen scenarios. Existing DG methods assume that the do-main la…

cs.CV2021★ 4 cited

Towards Corruption-Agnostic Robust Domain Adaptation

Yifan Xu, Kekai Sheng, Weiming Dong +3

Big progress has been achieved in domain adaptation in decades. Existing works are always based on an ideal assumption that testing target domain are i.i.d. with training target do…

cs.CV2021★ 5 cited

On Evolving Attention Towards Domain Adaptation

Kekai Sheng, Ke Li, Xiawu Zheng +5

Towards better unsupervised domain adaptation (UDA). Recently, researchers propose various domain-conditioned attention modules and make promising progresses. However, considering…