Search Results for author:
Found 3 papers, 2 papers with code
Part-aware Unified Representation of Language and Skeleton for Zero-shot Action Recognition
While remarkable progress has been made on supervised skeleton-based action recognition, the challenge of zero-shot recognition remains relatively unexplored.
Skeleton-OOD: An End-to-End Skeleton-Based Model for Robust Out-of-Distribution Human Action Detection
To address these challenges, we propose a novel end-to-end skeleton-based model called Skeleton-OOD, which is committed to improving the effectiveness of OOD tasks while ensuring the accuracy of ID recognition.
Adaptive Local-Component-aware Graph Convolutional Network for One-shot Skeleton-based Action Recognition
Skeleton-based action recognition receives increasing attention because the skeleton representations reduce the amount of training data by eliminating visual information irrelevant to actions.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
