122 citations · 311 across the 25 of their papers we have counts for
4 papers · 1 filter
Deep Learning for Video Anomaly Detection: A Review
Peng Wu, Chengyu Pan, Yuting Yan +3
Video anomaly detection (VAD) aims to discover behaviors or events deviating from the normality in videos. As a long-standing task in the field of computer vision, VAD has witnesse…
Weakly Supervised Video Anomaly Detection and Localization with Spatio-Temporal Prompts
Peng Wu, Xuerong Zhou, Guansong Pang +4
Current weakly supervised video anomaly detection (WSVAD) task aims to achieve frame-level anomalous event detection with only coarse video-level annotations available. Existing wo…
C3L: Content Correlated Vision-Language Instruction Tuning Data Generation via Contrastive Learning
Ji Ma, Wei Suo, Peng Wang +1
Vision-Language Instruction Tuning (VLIT) is a critical training phase for Large Vision-Language Models (LVLMs). With the improving capabilities of open-source LVLMs, researchers h…
Visual Prompt Tuning in Null Space for Continual Learning
Yue Lu, Shizhou Zhang, De Cheng +4
Existing prompt-tuning methods have demonstrated impressive performances in continual learning (CL), by selecting and updating relevant prompts in the vision-transformer models. On…