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
Multi Receptive Field Network for Semantic Segmentation	Jianlong Yuan, Zelu Deng, Shu Wang	2020	arxiv 2011.08577
Depth-Adapted CNNs for RGB-D Semantic Segmentation	Zongwei Wu, Guillaume Allibert, Christophe Stolz	2022	arxiv 2206.03939
CNN-aware Binary Map for General Semantic Segmentation	Mahdyar Ravanbakhsh, Hossein Mousavi, Moin Nabi	2016	arxiv 1609.09220
RHRSegNet: Relighting High-Resolution Night-Time Semantic Segmentation	Sarah Elmahdy, Rodaina Hebishy, Ali Hamdi	2024	arxiv 2407.06016
Neural Field Conditioning Strategies for 2D Semantic Segmentation	Martin Gromniak, Sven Magg, Stefan Wermter	2023	arxiv 2304.14371
Co-Training for Unsupervised Domain Adaptation of Semantic Segmentation Models	Jose L. Gómez, Gabriel Villalonga, Antonio M. López	2022	arxiv 2205.15781
BiCANet: Bi-directional Contextual Aggregating Network for Image Semantic Segmentation	Quan Zhou, Dechun Cong, Bin Kang	2020	arxiv 2003.09669
SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation	Qinghui Liu, Michael Kampffmeyer, Robert Jenssen	2020	arxiv 2009.01599
An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation	Jihan Yang, Ruijia Xu, Ruiyu Li	2019	arxiv 1912.08954
NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentation	Jianfeng Wang, Daniela Massiceti, Xiaolin Hu	2023	arxiv 2308.02866