4 citations · 5 across the 8 of their papers we have counts for
5 papers · 1 filter
Spectral Scalpel: Amplifying Adjacent Action Discrepancy via Frequency-Selective Filtering for Skeleton-Based Action Segmentation
Haoyu Ji, Bowen Chen, Zhihao Yang +6
Skeleton-based Temporal Action Segmentation (STAS) seeks to densely segment and classify diverse actions within long, untrimmed skeletal motion sequences. However, existing STAS me…
LaDy: Lagrangian-Dynamic Informed Network for Skeleton-based Action Segmentation via Spatial-Temporal Modulation
Haoyu Ji, Xueting Liu, Yu Gao +5
Skeleton-based Temporal Action Segmentation (STAS) aims to densely parse untrimmed skeletal sequences into frame-level action categories. However, existing methods, while proficien…
Text-Derived Relational Graph-Enhanced Network for Skeleton-Based Action Segmentation
Haoyu Ji, Bowen Chen, Weihong Ren +4
Skeleton-based Temporal Action Segmentation (STAS) aims to segment and recognize various actions from long, untrimmed sequences of human skeletal movements. Current STAS methods ty…
Language-Assisted Human Part Motion Learning for Skeleton-Based Temporal Action Segmentation
Bowen Chen, Haoyu Ji, Zhiyong Wang +5
Skeleton-based Temporal Action Segmentation involves the dense action classification of variable-length skeleton sequences. Current approaches primarily apply graph-based networks…
Exploring Self- and Cross-Triplet Correlations for Human-Object Interaction Detection
Weibo Jiang, Weihong Ren, Jiandong Tian +3
Human-Object Interaction (HOI) detection plays a vital role in scene understanding, which aims to predict the HOI triplet in the form of <human, object, action>. Existing methods m…