3 papers
cs.CV2025
Towards Open-World Human Action Segmentation Using Graph Convolutional Networks
Hao Xing, Kai Zhe Boey, Gordon Cheng
Human-object interaction segmentation is a fundamental task of daily activity understanding, which plays a crucial role in applications such as assistive robotics, healthcare, and…
cs.CV2025
Multi-Modal Graph Convolutional Network with Sinusoidal Encoding for Robust Human Action Segmentation
Hao Xing, Kai Zhe Boey, Yuankai Wu +2
Accurate temporal segmentation of human actions is critical for intelligent robots in collaborative settings, where a precise understanding of sub-activity labels and their tempora…
cs.RO2024
Understanding Human Activity with Uncertainty Measure for Novelty in Graph Convolutional Networks
Hao Xing, Darius Burschka
Understanding human activity is a crucial aspect of developing intelligent robots, particularly in the domain of human-robot collaboration. Nevertheless, existing systems encounter…