3 papers
cs.CV2024
Cross-Domain Learning for Video Anomaly Detection with Limited Supervision
Yashika Jain, Ali Dabouei, Min Xu
Video Anomaly Detection (VAD) automates the identification of unusual events, such as security threats in surveillance videos. In real-world applications, VAD models must effective…
cs.CV2024
Distilling Aggregated Knowledge for Weakly-Supervised Video Anomaly Detection
Jash Dalvi, Ali Dabouei, Gunjan Dhanuka +1
Video anomaly detection aims to develop automated models capable of identifying abnormal events in surveillance videos. The benchmark setup for this task is extremely challenging d…
cs.CV2023
Leveraging Generative Language Models for Weakly Supervised Sentence Component Analysis in Video-Language Joint Learning
Zaber Ibn Abdul Hakim, Najibul Haque Sarker, Rahul Pratap Singh +3
A thorough comprehension of textual data is a fundamental element in multi-modal video analysis tasks. However, recent works have shown that the current models do not achieve a com…