activity
20202024
most citedLocalizing Anomalies from Weakly-Labeled Videos

193 citations · 283 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2024★ 15 cited

Contrastive Learning of Person-independent Representations for Facial Action Unit Detection

Yong Li, Shiguang Shan

Facial action unit (AU) detection, aiming to classify AU present in the facial image, has long suffered from insufficient AU annotations. In this paper, we aim to mitigate this dat…

cs.CV2023★ 10 cited

Decoupled Multimodal Distilling for Emotion Recognition

Yong Li, Yuanzhi Wang, Zhen Cui

Human multimodal emotion recognition (MER) aims to perceive human emotions via language, visual and acoustic modalities. Despite the impressive performance of previous MER approach…

cs.NI2021★ 3 cited

Going Deeper in Frequency Convolutional Neural Network: A Theoretical Perspective

Xiaohan Zhu, Zhen Cui, Tong Zhang +2

Convolutional neural network (CNN) is one of the most widely-used successful architectures in the era of deep learning. However, the high-computational cost of CNN still hampers mo…

cs.CV2021★ 10 cited

Learning Fair Face Representation With Progressive Cross Transformer

Yong Li, Yufei Sun, Zhen Cui +2

Face recognition (FR) has made extraordinary progress owing to the advancement of deep convolutional neural networks. However, demographic bias among different racial cohorts still…

cs.CV2021★ 24 cited

Graph Jigsaw Learning for Cartoon Face Recognition

Yong Li, Lingjie Lao, Zhen Cui +2

Cartoon face recognition is challenging as they typically have smooth color regions and emphasized edges, the key to recognize cartoon faces is to precisely perceive their sparse a…

cs.CV2021★ 4 cited

Consistent Instance False Positive Improves Fairness in Face Recognition

Xingkun Xu, Yuge Huang, Pengcheng Shen +5

Demographic bias is a significant challenge in practical face recognition systems. Existing methods heavily rely on accurate demographic annotations. However, such annotations are…

cs.CV2021

Meta Auxiliary Learning for Facial Action Unit Detection

Yong Li, Shiguang Shan

Despite the success of deep neural networks on facial action unit (AU) detection, better performance depends on a large number of training images with accurate AU annotations. Howe…

cs.CV2021★ 15 cited

Learning Normal Dynamics in Videos with Meta Prototype Network

Hui Lv, Chen Chen, Zhen Cui +3

Frame reconstruction (current or future frame) based on Auto-Encoder (AE) is a popular method for video anomaly detection. With models trained on the normal data, the reconstructio…

cs.CV2021★ 9 cited

SDD-FIQA: Unsupervised Face Image Quality Assessment with Similarity Distribution Distance

Fu-Zhao Ou, Xingyu Chen, Ruixin Zhang +6

In recent years, Face Image Quality Assessment (FIQA) has become an indispensable part of the face recognition system to guarantee the stability and reliability of recognition perf…

cs.CV2020★ 193 cited

Localizing Anomalies from Weakly-Labeled Videos

Hui Lv, Chuanwei Zhou, Chunyan Xu +2

Video anomaly detection under video-level labels is currently a challenging task. Previous works have made progresses on discriminating whether a video sequencecontains anomalies.…