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cs.CV2025
Pistachio: Towards Synthetic, Balanced, and Long-Form Video Anomaly Benchmarks
Jie Li, Hongyi Cai, Mingkang Dong +4
Automatically detecting abnormal events in videos is crucial for modern autonomous systems, yet existing Video Anomaly Detection (VAD) benchmarks lack the scene diversity, balanced…
cs.CV2025
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…
cs.CV2025
Compact Attention: Exploiting Structured Spatio-Temporal Sparsity for Fast Video Generation
Qirui Li, Guangcong Zheng, Qi Zhao +4
The computational demands of self-attention mechanisms pose a critical challenge for transformer-based video generation, particularly in synthesizing ultra-long sequences. Current…