From the 1 of 4 linked papers with an AI index.
4 papers
Knowledge-guided Disentanglement with Atomic Actions for Action Recognition
Tianci Wu, Siqi Cao, Guangming Zhu +6
The paper introduces a framework that uses large language models to break down action labels into atomic actions and injects this semantic knowledge into video features to improve…
SkeletonContext: Skeleton-side Context Prompt Learning for Zero-Shot Skeleton-based Action Recognition
Ning Wang, Tieyue Wu, Naeha Sharif +5
Zero-shot skeleton-based action recognition aims to recognize unseen actions by transferring knowledge from seen categories through semantic descriptions. Most existing methods typ…
Prompt-guided Disentangled Representation for Action Recognition
Tianci Wu, Guangming Zhu, Jiang Lu +4
Action recognition is a fundamental task in video understanding. Existing methods typically extract unified features to process all actions in one video, which makes it challenging…
Multi-Granularity Mutual Refinement Network for Zero-Shot Learning
Ning Wang, Long Yu, Cong Hua +5
Zero-shot learning (ZSL) aims to recognize unseen classes with zero samples by transferring semantic knowledge from seen classes. Current approaches typically correlate global visu…