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
Computationally Efficient Wasserstein Loss for Structured Labels	Ayato Toyokuni, Sho Yokoi, Hisashi Kashima	2021	arxiv 2103.00899
Digital Twin Generation from Visual Data: A Survey	Andrew Melnik, Benjamin Alt, Giang Nguyen	2025	arxiv 2504.13159
BIMStruct3D: A Fully Automated Hybrid Learning Scan-to-BIM Pipeline with Integrated Topology Refinement	Mahdi Chamseddine, Fabian Kaufmann, Marius Schellen	2026	arxiv 2604.24311
Dilated Neighborhood Attention Transformer	Ali Hassani, Humphrey Shi	2022	arxiv 2209.15001
{\Omega}-Net (Omega-Net): Fully Automatic, Multi-View Cardiac MR Detection, Orientation, and Segmentation with Deep Neural Networks	Davis M. Vigneault, Weidi Xie, Carolyn Y. Ho	2017	arxiv 1711.01094
Segmentation of Cellular Patterns in Confocal Images of Melanocytic Lesions in vivo via a Multiscale Encoder-Decoder Network (MED-Net)	Kivanc Kose, Alican Bozkurt, Christi Alessi-Fox	2020	arxiv 2001.01005
SINet: Extreme Lightweight Portrait Segmentation Networks with Spatial Squeeze Modules and Information Blocking Decoder	Hyojin Park, Lars Lowe Sjösund, YoungJoon Yoo	2019	arxiv 1911.09099
DEEVA: A Deep Learning and IoT Based Computer Vision System to Address Safety and Security of Production Sites in Energy Industry	Nimish M. Awalgaonkar, Haining Zheng, Christopher S. Gurciullo	2020	arxiv 2003.01196
LID 2020: The Learning from Imperfect Data Challenge Results	Yunchao Wei, Shuai Zheng, Ming-Ming Cheng	2020	arxiv 2010.11724
Learning 3D Semantics from Pose-Noisy 2D Images with Hierarchical Full Attention Network