PYSKL: a toolbox for skeleton-based video understanding
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Skeleton Based Action RecognitionVideo UnderstandingSimilar Papers 제목 키워드 기반
PYSKL: Towards Good Practices for Skeleton Action Recognition
We present PYSKL: an open-source toolbox for skeleton-based action recognition based on PyTorch. The toolbox supports a wide variety of skeleton action recognition algorithms, including approaches based on GCN and CNN. I…
Action RecognitionSkeleton Based Action RecognitionLearning by Aligning 2D Skeleton Sequences and Multi-Modality Fusion
This paper presents a self-supervised temporal video alignment framework which is useful for several fine-grained human activity understanding applications. In contrast with the state-of-the-art method of CASA, where seq…
RetrievalSelf-Supervised LearningVideo AlignmentSkeletons Speak Louder than Text: A Motion-Aware Pretraining Paradigm for Video-Based Person Re-Identification
Multimodal pretraining has revolutionized visual understanding, but its impact on video-based person re-identification (ReID) remains underexplored. Existing approaches often rely on video-text pairs, yet suffer from two…
Person Re-IdentificationRepresentation LearningContrastive LearningCausal Discovery Toolbox: Uncover causal relationships in Python
This paper presents a new open source Python framework for causal discovery from observational data and domain background knowledge, aimed at causal graph and causal mechanism modeling. The 'cdt' package implements the e…
Causal DiscoveryT-MOR: Learning Motion-Aware Skeleton Representations for Human Action Recognition
Vision-language models such as CLIP have recently achieved strong performance on a wide range of visual understanding tasks. However, most existing models rely primarily on appearance-level supervision from images or vid…
Action ClassificationContrastive LearningAction UnderstandingAction Recognition