Holmes-VAD: Towards Unbiased and Explainable Video Anomaly Detection via
Multi-modal LLM

Holmes-VAD: Towards Unbiased and Explainable Video Anomaly Detection via Multi-modal LLM

18 June 2024

Huaxin Zhang

Jialong Zuo

Papers citing "Holmes-VAD: Towards Unbiased and Explainable Video Anomaly Detection via Multi-modal LLM"

8 / 8 papers shown

Title
Omni-SILA: Towards Omni-scene Driven Visual Sentiment Identifying, Locating and Attributing in Videos Jiamin Luo Jingjing Wang Junxiao Ma Yujie Jin Shoushan Li Guodong Zhou 31 0 0 26 Feb 2025
Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey Ruiyao Xu Kaize Ding 50 5 0 17 Feb 2025
Detecting Contextual Anomalies by Discovering Consistent Spatial Regions Zhengye Yang Richard J. Radke 43 0 0 14 Jan 2025
Do Language Models Understand Time? Xi Ding Lei Wang 162 0 0 18 Dec 2024
Deep Learning for Video Anomaly Detection: A Review Peng Wu Chengyu Pan Yuting Yan Guansong Pang Peng Wang Yanning Zhang VLM AI4TS 37 6 0 09 Sep 2024
Networking Systems for Video Anomaly Detection: A Tutorial and Survey Jing Liu Yang Liu Jieyu Lin Jielin Li Peng Sun Bo Hu Liang Song Azzedine Boukerche Victor C.M. Leung Victor C.M. Leung 43 10 0 16 May 2024
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection Bin Lin Yang Ye Bin Zhu Jiaxi Cui Munan Ning Peng Jin Li-ming Yuan VLM MLLM 194 576 0 16 Nov 2023
mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality Qinghao Ye Haiyang Xu Guohai Xu Jiabo Ye Ming Yan ... Junfeng Tian Qiang Qi Ji Zhang Feiyan Huang Jingren Zhou VLM MLLM 203 883 0 27 Apr 2023