4 citations · 7 across the 5 of their papers we have counts for
5 papers
How Much Temporal Long-Term Context is Needed for Action Segmentation?
Emad Bahrami, Gianpiero Francesca, Juergen Gall
Modeling long-term context in videos is crucial for many fine-grained tasks including temporal action segmentation. An interesting question that is still open is how much long-term…
Automatic off-line design of robot swarms: exploring the transferability of control software and design methods across different platforms
Miquel Kegeleirs, David Garzón Ramos, Lorenzo Garattoni +2
Automatic off-line design is an attractive approach to implementing robot swarms. In this approach, a designer specifies a mission for the swarm, and an optimization process genera…
Self-Supervised Video Representation Learning via Latent Time Navigation
Di Yang, Yaohui Wang, Quan Kong +4
Self-supervised video representation learning aimed at maximizing similarity between different temporal segments of one video, in order to enforce feature persistence over time. Th…
Human-Scene Network: A Novel Baseline with Self-rectifying Loss for Weakly supervised Video Anomaly Detection
Snehashis Majhi, Rui Dai, Quan Kong +3
Video anomaly detection in surveillance systems with only video-level labels (i.e. weakly-supervised) is challenging. This is due to, (i) the complex integration of human and scene…
ViA: View-invariant Skeleton Action Representation Learning via Motion Retargeting
Di Yang, Yaohui Wang, Antitza Dantcheva +3
Current self-supervised approaches for skeleton action representation learning often focus on constrained scenarios, where videos and skeleton data are recorded in laboratory setti…