Haojin Li — accepted AI-conference papers

2026

DeLightMono: Enhancing Self-Supervised Monocular Depth Estimation in Endoscopy by Decoupling Uneven Illumination

Mingyang Ou, Haojin Li, Yifeng Zhang, Ke Niu, Zhongxi Qiu, Heng Li +1

AAAI 2026technical

Self-supervised monocular depth estimation serves as a key task in the development of endoscopic navigation systems. However, performance degradation persists due to uneven illumination inherent in endoscopic images, particularly in low-intensity regions. Existing low-light enhancement techniques fa

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2025

AIF-SFDA: Autonomous Information Filter Driven Source-Free Domain Adaptation for Medical Image Segmentation

Haojin Li, Heng Li, Jianyu Chen, Rihan Zhong, Ke Niu, Huazhu Fu +1

AAAI 2025technical

Decoupling domain-variant information (DVI) from domain-invariant information (DII) serves as a prominent strategy for mitigating domain shifts in the practical implementation of deep learning algorithms. However, in medical settings, concerns surrounding data collection and privacy often restrict a…

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