Kaiwen Huang — accepted AI-conference papers

2026

Bidirectional Channel-selective Semantic Interaction for Semi-Supervised Medical Segmentation

Kaiwen Huang, Yizhe Zhang, Yi Zhou, Tianyang Xu, Tao Zhou

AAAI 2026technical

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 teacher and dual-stream consistency learning. These approaches often face issues like error accumulation and model structural

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2026

SemiGDA: Generative Dual-distribution Alignment for Semi-Supervised Medical Image Segmentation

Kaiwen Huang, Yi Zhou, Yizhe Zhang, Jingxiong Li, Tao Zhou

CVPR 2026

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 performance. Traditional discriminative segmentation relies on segmentation masks, neglecting feature-level distribution c

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