Shumeng Li — accepted AI-conference papers

2026

Duala: Dual-Level Alignment of Subjects and Stimuli for Cross-Subject fMRI Decoding

Shumeng Li, Jintao Guo, Jian Zhang, Yulin Zhou, Luyang Cao, Yinghuan Shi

CVPR 2026

Cross-subject visual decoding aims to reconstruct visual experiences from brain activity across individuals, enabling more scalable and practical brain-computer interfaces. However, existing methods often suffer from degraded performance when adapting to new subjects with limited data, as they strug

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2023

Orthogonal Annotation Benefits Barely-Supervised Medical Image Segmentation

Heng Cai, Shumeng Li, Lei Qi, Qian Yu, Yinghuan Shi, Yang Gao

CVPR 2023poster

Recent trends in semi-supervised learning have significantly boosted the performance of 3D semi-supervised medical image segmentation. Compared with 2D images, 3D medical volumes involve information from different directions, e.g., transverse, sagittal, and coronal planes, so as to naturally provide…

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