most citedDeep Frequent Spatial Temporal Learning for Face Anti-Spoofing

11 citations · 17 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20204 cited

Online Knowledge Distillation via Multi-branch Diversity Enhancement

Zheng Li, Ying Huang, Defang Chen +3

Knowledge distillation is an effective method to transfer the knowledge from the cumbersome teacher model to the lightweight student model. Online knowledge distillation uses the e…

cs.CV20202 cited

More Information Supervised Probabilistic Deep Face Embedding Learning

Ying Huang, Shangfeng Qiu, Wenwei Zhang +2

Researches using margin based comparison loss demonstrate the effectiveness of penalizing the distance between face feature and their corresponding class centers. Despite their pop…

cs.CV2020

Joint Deep Learning of Facial Expression Synthesis and Recognition

Yan Yan, Ying Huang, Si Chen +2

Recently, deep learning based facial expression recognition (FER) methods have attracted considerable attention and they usually require large-scale labelled training data. Nonethe…

cs.CV202011 cited

Deep Frequent Spatial Temporal Learning for Face Anti-Spoofing

Ying Huang, Wenwei Zhang, Jinzhuo Wang

Face anti-spoofing is crucial for the security of face recognition system, by avoiding invaded with presentation attack. Previous works have shown the effectiveness of using depth…

cs.CV2019

Multi-Level Network for High-Speed Multi-Person Pose Estimation

Ying Huang, Jiankai Zhuang, Zengchang Qin

In multi-person pose estimation, the left/right joint type discrimination is always a hard problem because of the similar appearance. Traditionally, we solve this problem by stacki…

cs.CV2019

FollowMeUp Sports: New Benchmark for 2D Human Keypoint Recognition

Ying Huang, Bin Sun, Haipeng Kan +2

Human pose estimation has made significant advancement in recent years. However, the existing datasets are limited in their coverage of pose variety. In this paper, we introduce a…