5 citations · 13 across the 9 of their papers we have counts for
3 papers · 1 filter
DyAnNet: A Scene Dynamicity Guided Self-Trained Video Anomaly Detection Network
Kamalakar Thakare, Yash Raghuwanshi, Debi Prosad Dogra +2
Unsupervised approaches for video anomaly detection may not perform as good as supervised approaches. However, learning unknown types of anomalies using an unsupervised approach is…
Dual Prototype Attention for Unsupervised Video Object Segmentation
Suhwan Cho, Minhyeok Lee, Seunghoon Lee +4
Unsupervised video object segmentation (VOS) aims to detect and segment the most salient object in videos. The primary techniques used in unsupervised VOS are 1) the collaboration…
Probabilistic Representations for Video Contrastive Learning
Jungin Park, Jiyoung Lee, Ig-Jae Kim +1
This paper presents Probabilistic Video Contrastive Learning, a self-supervised representation learning method that bridges contrastive learning with probabilistic representation.…