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cs.CV2026
Fine-Grained Post-Training Quantization for Large Vision Language Models with Quantization-Aware Integrated Gradients
Ziwei Xiang, Fanhu Zeng, Hongjian Fang +6
Large Vision Language Models (LVLMs) have achieved remarkable success in a range of downstream tasks that require multimodal interaction, but their capabilities come with substanti…
cs.CV2025★ 1 cited
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…
cs.CV2025
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…