33 citations · 38 across the 10 of their papers we have counts for
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cs.CV2026
Adaptive Augmentation-Aware Latent Learning for Robust LiDAR Semantic Segmentation
Wangkai Li, Zhaoyang Li, Yuwen Pan +3
Adverse weather conditions significantly degrade the performance of LiDAR point cloud semantic segmentation networks by introducing large distribution shifts. Existing augmentation…
cs.CV2026
DA-Cal: Towards Cross-Domain Calibration in Semantic Segmentation
Wangkai Li, Rui Sun, Zhaoyang Li +2
While existing unsupervised domain adaptation (UDA) methods greatly enhance target domain performance in semantic segmentation, they often neglect network calibration quality, resu…
cs.CV2026
Towards Robust Pseudo-Label Learning in Semantic Segmentation: An Encoding Perspective
Wangkai Li, Rui Sun, Zhaoyang Li +1
Pseudo-label learning is widely used in semantic segmentation, particularly in label-scarce scenarios such as unsupervised domain adaptation (UDA) and semisupervised learning (SSL)…