activity
20242026
most citedGLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Cluster-Wise Spatio-Temporal Masking for Efficient Video-Language Pretraining

Weijun Zhuang, Yuqing Huang, Weikang Meng +5

Large-scale video-language pretraining enables strong generalization across multimodal tasks but often incurs prohibitive computational costs. Although recent advances in masked vi…

cs.CV2025★ 1 cited

MEGC2025: Micro-Expression Grand Challenge on Spot Then Recognize and Visual Question Answering

Xinqi Fan, Jingting Li, John See +6

Facial micro-expressions (MEs) are involuntary movements of the face that occur spontaneously when a person experiences an emotion but attempts to suppress or repress the facial ex…

cs.CV2025

Grounding-MD: Grounded Video-language Pre-training for Open-World Moment Detection

Weijun Zhuang, Qizhang Li, Xin Li +5

Temporal Action Detection and Moment Retrieval constitute two pivotal tasks in video understanding, focusing on precisely localizing temporal segments corresponding to specific act…

cs.CV2024

Multi-modal Crowd Counting via a Broker Modality

Haoliang Meng, Xiaopeng Hong, Chenhao Wang +2

Multi-modal crowd counting involves estimating crowd density from both visual and thermal/depth images. This task is challenging due to the significant gap between these distinct m…

cs.CV2024★ 3 cited

GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection

Hang Yao, Ming Liu, Haolin Wang +4

Diffusion models have shown superior performance on unsupervised anomaly detection tasks. Since trained with normal data only, diffusion models tend to reconstruct normal counterpa…