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I Seek You in Videos: Identity-Conditioned Queries for Person-Centric Video Reasoning
Shibo Gao, Chongxiao Wang, Chenglong Huang +10
Real-world video reasoning often involves multimodal, multi-source inputs, whereas existing video reasoning tasks typically assume a simplified video-text setting, limiting identit…
The Evolution of Video Anomaly Detection: A Unified Framework from DNN to MLLM
Shibo Gao, Peipei Yang, Haiyang Guo +7
Video anomaly detection (VAD) aims to identify and ground anomalous behaviors or events in videos, serving as a core technology in the fields of intelligent surveillance and public…
VAGU & GtS: LLM-Based Benchmark and Framework for Joint Video Anomaly Grounding and Understanding
Shibo Gao, Peipei Yang, Yangyang Liu +4
Video Anomaly Detection (VAD) aims to identify anomalous events in videos and accurately determine their time intervals. Current VAD methods mainly fall into two categories: tradit…
Recoverable Compression: A Multimodal Vision Token Recovery Mechanism Guided by Text Information
Yi Chen, Jian Xu, Xu-Yao Zhang +3
With the advancement of large-scale language modeling techniques, large multimodal models combining visual encoders with large language models have demonstrated exceptional perform…