Hawk: Learning to Understand Open-World Video Anomalies

Hawk: Learning to Understand Open-World Video Anomalies

27 May 2024

Xiaogang Xu

Jiangbo Lu

Papers citing "Hawk: Learning to Understand Open-World Video Anomalies"

7 / 7 papers shown

Title
EchoInk-R1: Exploring Audio-Visual Reasoning in Multimodal LLMs via Reinforcement Learning Zhenghao Xing Xiaowei Hu Chi-Wing Fu W. Wang Jifeng Dai Pheng-Ann Heng MLLM OffRL VLM LRM 38 0 0 07 May 2025
Uncertainty-Weighted Image-Event Multimodal Fusion for Video Anomaly Detection SungHeon Jeong Jihong Park Mohsen Imani 43 0 0 05 May 2025
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 185 576 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
Tag2Text: Guiding Vision-Language Model via Image Tagging Xinyu Huang Youcai Zhang Jinyu Ma Weiwei Tian Rui Feng Yuejie Zhang Yaqian Li Yandong Guo Lei Zhang CLIP MLLM VLM 3DV 59 73 0 10 Mar 2023
BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models Junnan Li Dongxu Li Silvio Savarese Steven C. H. Hoi VLM MLLM 244 4,186 0 30 Jan 2023