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cs.CV2026
Uncovering What, Why and How: A Comprehensive Benchmark for Causation Understanding of Video Anomaly
Hang Du, Sicheng Zhang, Binzhu Xie +16
Video anomaly understanding (VAU) aims to automatically comprehend unusual occurrences in videos, thereby enabling various applications such as traffic surveillance and industrial…
cs.CV2025
From Easy to Hard: The MIR Benchmark for Progressive Interleaved Multi-Image Reasoning
Hang Du, Jiayang Zhang, Guoshun Nan +8
Multi-image Interleaved Reasoning aims to improve Multi-modal Large Language Models (MLLMs) ability to jointly comprehend and reason across multiple images and their associated tex…
cs.CV2024
Exploring What Why and How: A Multifaceted Benchmark for Causation Understanding of Video Anomaly
Hang Du, Guoshun Nan, Jiawen Qian +7
Recent advancements in video anomaly understanding (VAU) have opened the door to groundbreaking applications in various fields, such as traffic monitoring and industrial automation…