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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.CV2024
TP-UNet: Temporal Prompt Guided UNet for Medical Image Segmentation
Ranmin Wang, Limin Zhuang, Hongkun Chen +2
The advancement of medical image segmentation techniques has been propelled by the adoption of deep learning techniques, particularly UNet-based approaches, which exploit semantic…