3 papers
cs.CV2025
Learning to Tell Apart: Weakly Supervised Video Anomaly Detection via Disentangled Semantic Alignment
Wenti Yin, Huaxin Zhang, Xiang Wang +7
Recent advancements in weakly-supervised video anomaly detection have achieved remarkable performance by applying the multiple instance learning paradigm based on multimodal founda…
cs.CV2025
Holmes-VAU: Towards Long-term Video Anomaly Understanding at Any Granularity
Huaxin Zhang, Xiaohao Xu, Xiang Wang +6
How can we enable models to comprehend video anomalies occurring over varying temporal scales and contexts? Traditional Video Anomaly Understanding (VAU) methods focus on frame-lev…
cs.CV2024
Structural Pruning via Spatial-aware Information Redundancy for Semantic Segmentation
Dongyue Wu, Zilin Guo, Li Yu +2
In recent years, semantic segmentation has flourished in various applications. However, the high computational cost remains a significant challenge that hinders its further adoptio…