SOTA2 Research · papers

Papers for “semantic segmentation”

Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.

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20 indexed

Title	Authors	Year	Source
Continual Attentive Fusion for Incremental Learning in Semantic Segmentation	Guanglei Yang, Enrico Fini, Dan Xu	2022	arxiv 2202.00432
Striking the Right Balance: Recall Loss for Semantic Segmentation	Junjiao Tian, Niluthpol Mithun, Zach Seymour	2021	arxiv 2106.14917
COVERED, CollabOratiVE Robot Environment Dataset for 3D Semantic segmentation	Charith Munasinghe, Fatemeh Mohammadi Amin, Davide Scaramuzza	2023	arxiv 2302.12656
Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes	Yang Zhang, Philip David, Boqing Gong	2017	arxiv 1707.09465
Bi-directional Contrastive Learning for Domain Adaptive Semantic Segmentation	Geon Lee, Chanho Eom, Wonkyung Lee	2022	arxiv 2207.10892
HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation	Lukas Hoyer, Dengxin Dai, Luc Van Gool	2022	arxiv 2204.13132
Triple-View Knowledge Distillation for Semi-Supervised Semantic Segmentation	Ping Li, Junjie Chen, Li Yuan	2023	arxiv 2309.12557
Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation	Bowen Zhang, Yifan Liu, Zhi Tian	2021	arxiv 2107.14428
Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation	Qin Wang, Dengxin Dai, Lukas Hoyer	2021	arxiv 2104.13613
Temporal-aware Hierarchical Mask Classification for Video Semantic Segmentation	Zhaochong An, Guolei Sun, Zongwei Wu	2023	arxiv 2309.08020