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Changqi Wang

2 accepted papers

2023

Boosting Semi-Supervised Semantic Segmentation with Probabilistic Representations

AAAI 2023technical

Recent breakthroughs in semi-supervised semantic segmentation have been developed through contrastive learning. In prevalent pixel-wise contrastive learning solutions, the model maps pixels to deterministic representations and regularizes them in the latent space. However, there exist inaccurate pse…

2023

Space Engage: Collaborative Space Supervision for Contrastive-Based Semi-Supervised Semantic Segmentation

ICCV 2023poster

Semi-Supervised Semantic Segmentation (S4) aims to train a segmentation model with limited labeled images and a substantial volume of unlabeled images. To improve the robustness of representations, powerful methods introduce a pixel-wise contrastive learning approach in latent space (i.e., represent…

Cited by 18PDFScholar