54 citations · 74 across the 17 of their papers we have counts for
5 papers · 1 filter
CueBench: Advancing Unified Understanding of Context-Aware Video Anomalies in Real-World
Yating Yu, Congqi Cao, Zhaoying Wang +6
How far are deep models from real-world video anomaly understanding (VAU)? Current works typically emphasize on detecting unexpected occurrences deviated from normal patterns or co…
Autoregressive Denoising Score Matching is a Good Video Anomaly Detector
Hanwen Zhang, Congqi Cao, Qinyi Lv +2
Video anomaly detection (VAD) is an important computer vision problem. Thanks to the mode coverage capabilities of generative models, the likelihood-based paradigm is catching grow…
Vision and Intention Boost Large Language Model in Long-Term Action Anticipation
Congqi Cao, Lanshu Hu, Yating Yu +1
Long-term action anticipation (LTA) aims to predict future actions over an extended period. Previous approaches primarily focus on learning exclusively from video data but lack pri…
Task-Adapter++: Task-specific Adaptation with Order-aware Alignment for Few-shot Action Recognition
Congqi Cao, Peiheng Han, Yueran zhang +4
Large-scale pre-trained models have achieved remarkable success in language and image tasks, leading an increasing number of studies to explore the application of pre-trained image…
Learning to Generalize without Bias for Open-Vocabulary Action Recognition
Yating Yu, Congqi Cao, Yifan Zhang +1
Leveraging the effective visual-text alignment and static generalizability from CLIP, recent video learners adopt CLIP initialization with further regularization or recombination f…