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20182022
most citedSpatiotemporal Recurrent Convolutional Networks for Recognizing Spontaneous Micro-expressions

17 citations · 36 across the 5 of their papers we have counts for

collaborators

6 papers

cs.GT2022

Stateful Detection of Adversarial Reprogramming

Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia +5

Adversarial reprogramming allows stealing computational resources by repurposing machine learning models to perform a different task chosen by the attacker. For example, a model tr…

cs.CV202012 cited

Revisiting Pixel-Wise Supervision for Face Anti-Spoofing

Zitong Yu, Xiaobai Li, Jingang Shi +2

Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from the presentation attacks (PAs). As more and more realistic PAs with novel types spring up, it…

cs.CV20204 cited

Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition

Wei Peng, Jingang Shi, Zhaoqiang Xia +1

Graph Convolutional Networks (GCNs) have already demonstrated their powerful ability to model the irregular data, e.g., skeletal data in human action recognition, providing an exci…

cs.CV20193 cited

3D Face Mask Presentation Attack Detection Based on Intrinsic Image Analysis

Lei Li, Zhaoqiang Xia, Xiaoyue Jiang +3

Face presentation attacks have become a major threat to face recognition systems and many countermeasures have been proposed in the past decade. However, most of them are devoted t…

cs.CV201917 cited

Spatiotemporal Recurrent Convolutional Networks for Recognizing Spontaneous Micro-expressions

Zhaoqiang Xia, Xiaopeng Hong, Xingyu Gao +2

Recently, the recognition task of spontaneous facial micro-expressions has attracted much attention with its various real-world applications. Plenty of handcrafted or learned featu…

cs.CV2018

Face Presentation Attack Detection in Learned Color-liked Space

Lei Li, Zhaoqiang Xia, Xiaoyue Jiang +2

Face presentation attack detection (PAD) has become a thorny problem for biometric systems and numerous countermeasures have been proposed to address it. However, majority of them…