4 accepted papers
Vision-Language-Action (VLA) models have shown remarkable progress in embodied tasks recently, but most methods process visual observations independently at each timestep. This history-agnostic design treats robot manipulation as a Markov Decision Process, even though real-world robotic control is i
Scene boundary detection breaks down long videos into meaningful story-telling units and plays a crucial role in high-level video understanding. Despite significant advancements in this area, this task remains a challenging problem as it requires a comprehensive understanding of multimodal cues and…
Few-shot action recognition aims to recognize novel action classes (query) using just a few samples (support). The majority of current approaches follow the metric learning paradigm, which learns to compare the similarity between videos. Recently, it has been observed that directly measuring this si…
Weakly supervised temporal action detection aims to localize temporal boundaries of actions and identify their categories simultaneously with only video-level category labels during training. Among existing methods, attention-based methods have achieved superior performance by separating action and…