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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Fei Pan, Inkyu Shin, Francois Rameau |
| 2020 |
| arxiv 2004.07703 |
| Emerging Semantic Segmentation from Positive and Negative Coarse Label Learning | Le Zhang, Fuping Wu, Arun Thirunavukarasu | 2025 | arxiv 2508.18186 |
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| Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads | Andrew Yarovoi, Christopher R. Valenta | 2025 | arxiv 2508.20135 |
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| Extracting Uncertainty Estimates from Mixtures of Experts for Semantic Segmentation | Svetlana Pavlitska, Beyza Keskin, Alwin Fa\ssbender | 2025 | arxiv 2509.04816 |
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| I-Segmenter: Integer-Only Vision Transformer for Efficient Semantic Segmentation | Jordan Sassoon, Michal Szczepanski, Martyna Poreba | 2025 | arxiv 2509.10334 |
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| Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation | Guanglei Yang, Zhun Zhong, Hao Tang | 2021 | arxiv 2111.10339 |
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| Learning Local and Global Temporal Contexts for Video Semantic Segmentation | Guolei Sun, Yun Liu, Henghui Ding | 2022 | arxiv 2204.03330 |
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| CSRNet: Cascaded Selective Resolution Network for Real-time Semantic Segmentation | Jingjing Xiong, Lai-Man Po, Wing-Yin Yu | 2021 | arxiv 2106.04400 |
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| Learning Shape Priors by Pairwise Comparison for Robust Semantic Segmentation | Cong Xie, Hualuo Liu, Shilei Cao | 2022 | arxiv 2204.11090 |
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| Test-Time Training for Semantic Segmentation with Output Contrastive Loss | Yunlong Zhang, Yuxuan Sun, Sunyi Zheng | 2023 | arxiv 2311.07877 |
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| Few Clicks Suffice: Active Test-Time Adaptation for Semantic Segmentation | Longhui Yuan, Shuang Li, Zhuo He | 2023 | arxiv 2312.01835 |
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