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20182026
most citedPoseFace: Pose-Invariant Features and Pose-Adaptive Loss for Face Recognition

23 citations · 46 across the 11 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

cs.CV2021★ 1 cited

Makeup216: Logo Recognition with Adversarial Attention Representations

Junjun Hu, Yanhao Zhu, Bo Zhao +5

One of the challenges of logo recognition lies in the diversity of forms, such as symbols, texts or a combination of both; further, logos tend to be extremely concise in design whi…

cs.CV2021★ 3 cited

Consistency Regularization for Deep Face Anti-Spoofing

Zezheng Wang, Zitong Yu, Xun Wang +7

Face anti-spoofing (FAS) plays a crucial role in securing face recognition systems. Empirically, given an image, a model with more consistent output on different views of this imag…

cs.CV2021

Meta-Teacher For Face Anti-Spoofing

Yunxiao Qin, Zitong Yu, Longbin Yan +3

Face anti-spoofing (FAS) secures face recognition from presentation attacks (PAs). Existing FAS methods usually supervise PA detectors with handcrafted binary or pixel-wise labels.…

cs.CV2021★ 1 cited

3D High-Fidelity Mask Face Presentation Attack Detection Challenge

Ajian Liu, Chenxu Zhao, Zitong Yu +8

The threat of 3D masks to face recognition systems is increasingly serious and has been widely concerned by researchers. To facilitate the study of the algorithms, a large-scale Hi…

cs.CV2021★ 23 cited

PoseFace: Pose-Invariant Features and Pose-Adaptive Loss for Face Recognition

Qiang Meng, Xiaqing Xu, Xiaobo Wang +6

Despite the great success achieved by deep learning methods in face recognition, severe performance drops are observed for large pose variations in unconstrained environments (e.g.…

cs.CV2021

Deep Learning for Face Anti-Spoofing: A Survey

Zitong Yu, Yunxiao Qin, Xiaobai Li +3

Face anti-spoofing (FAS) has lately attracted increasing attention due to its vital role in securing face recognition systems from presentation attacks (PAs). As more and more real…