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-encoder ConvNeXt Network with Smooth Attentional Feature Fusion for Multispectral Semantic Segmentation	Leo Thomas Ramos, Angel D. Sappa	2026	arxiv 2602.10137
Prompt-Free and Efficient SAM2 Adaptation for Biomedical Semantic Segmentation via Dual Adapters	Hinako Mitsuoka, Kazuhiro Hotta	2026	arxiv 2605.05979
A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery	Aatif Jiwani, Shubhrakanti Ganguly, Chao Ding	2021	arxiv 2104.01263
On the Feasibility and Generality of Patch-based Adversarial Attacks on Semantic Segmentation Problems	Soma Kontar, Andras Horvath	2022	arxiv 2205.10539
Smaller3d: Smaller Models for 3D Semantic Segmentation Using Minkowski Engine and Knowledge Distillation Methods	Alen Adamyan, Erik Harutyunyan	2023	arxiv 2305.03188
Performance Evaluation of Deep Learning Networks for Semantic Segmentation of Traffic Stereo-Pair Images	Vlad Taran, Nikita Gordienko, Yuriy Kochura	2018	arxiv 1806.01896
Semantic Segmentation of Thigh Muscle using 2.5D Deep Learning Network Trained with Limited Datasets	Hasnine Haque, Masahiro Hashimoto, Nozomu Uetake	2019	arxiv 1911.09249
Weakly Supervised Semantic Segmentation of Satellite Images for Land Cover Mapping -- Challenges and Opportunities	Michael Schmitt, Jonathan Prexl, Patrick Ebel	2020	arxiv 2002.08254
MetaBox+: A new Region Based Active Learning Method for Semantic Segmentation using Priority Maps	Pascal Colling, Lutz Roese-Koerner, Hanno Gottschalk	2020	arxiv 2010.01884