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
MetaSeg: Content-Aware Meta-Net for Omni-Supervised Semantic Segmentation	Shenwang Jiang, Jianan Li, Ying Wang	2024	arxiv 2401.11738
SED: A Simple Encoder-Decoder for Open-Vocabulary Semantic Segmentation	Bin Xie, Jiale Cao, Jin Xie	2023	arxiv 2311.15537
m2caiSeg: Semantic Segmentation of Laparoscopic Images using Convolutional Neural Networks	Salman Maqbool, Aqsa Riaz, Hasan Sajid	2020	arxiv 2008.10134
Augmentation-Free Dense Contrastive Knowledge Distillation for Efficient Semantic Segmentation	Jiawei Fan, Chao Li, Xiaolong Liu	2023	arxiv 2312.04168
SEMNAV: Enhancing Visual Semantic Navigation in Robotics through Semantic Segmentation	Rafael Flor-Rodríguez, Carlos Gutiérrez-Álvarez, Francisco Javier Acevedo-Rodríguez	2025	arxiv 2506.01418
UCC: Uncertainty guided Cross-head Co-training for Semi-Supervised Semantic Segmentation	Jiashuo Fan, Bin Gao, Huan Jin	2022	arxiv 2205.10334
Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic Segmentation	Carolina Redondo-Cabrera, Marcos Baptista-Ríos, Roberto J. López-Sastre	2018	arxiv 1804.04882
Detecting Adversarial Attacks in Semantic Segmentation via Uncertainty Estimation: A Deep Analysis	Kira Maag, Roman Resner, Asja Fischer	2024	arxiv 2408.10021
Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation	Steven Landgraf, Markus Hillemann, Theodor Kapler	2024	arxiv 2402.10580
Optimizing rgb-d semantic segmentation through multi-modal interaction and pooling attention