2 papers
cs.CV2026
Hierarchical Action Learning for Weakly-Supervised Action Segmentation
Junxian Huang, Ruichu Cai, Hao Zhu +5
Humans perceive actions through key transitions that structure actions across multiple abstraction levels, whereas machines, relying on visual features, tend to over-segment. This…
cs.CV2025
Salient Concept-Aware Generative Data Augmentation
Tianchen Zhao, Xuanbai Chen, Zhihua Li +5
Recent generative data augmentation methods conditioned on both image and text prompts struggle to balance between fidelity and diversity, as it is challenging to preserve essentia…