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cs.CV2026
Spatial Lifting for Dense Prediction
Mingzhi Xu, Tao Zhou, Yong Li +1
We present Spatial Lifting (SL), a novel methodology for dense prediction tasks. SL operates by lifting standard inputs, such as 2D images, into a higher-dimensional space and subs…
cs.CV2026
SemiGDA: Generative Dual-distribution Alignment for Semi-Supervised Medical Image Segmentation
Kaiwen Huang, Yi Zhou, Yizhe Zhang +2
Semi-supervised learning addresses label scarcity and high annotation costs in medical image segmentation by exploiting the latent information in unlabeled data to enhance model pe…
cs.CV2026
Bidirectional Channel-selective Semantic Interaction for Semi-Supervised Medical Segmentation
Kaiwen Huang, Yizhe Zhang, Yi Zhou +2
Semi-supervised medical image segmentation is an effective method for addressing scenarios with limited labeled data. Existing methods mainly rely on frameworks such as mean teache…