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
Per-Pixel Feedback for improving Semantic Segmentation	Aditya Ganeshan	2017	arxiv 1712.02861
Training-Free Semantic Segmentation via LLM-Supervision	Wenfang Sun, Yingjun Du, Gaowen Liu	2024	arxiv 2404.00701
The Robust Semantic Segmentation UNCV2023 Challenge Results	Xuanlong Yu, Yi Zuo, Zitao Wang	2023	arxiv 2309.15478
Few-shot 3D Point Cloud Semantic Segmentation	Na Zhao, Tat-Seng Chua, Gim Hee Lee	2020	arxiv 2006.12052
Single-Step Adversarial Training for Semantic Segmentation	Daniel Wiens, Barbara Hammer	2021	arxiv 2106.15998
GPS-GLASS: Learning Nighttime Semantic Segmentation Using Daytime Video and GPS data	Hongjae Lee, Changwoo Han, Jun-Sang Yoo	2022	arxiv 2207.13297
Satellite Image Semantic Segmentation	Eric Guérin, Killian Oechslin, Christian Wolf	2021	arxiv 2110.05812
Self-Supervised Difference Detection for Weakly-Supervised Semantic Segmentation	Wataru Shimoda, Keiji Yanai	2019	arxiv 1911.01370
Decoder Denoising Pretraining for Semantic Segmentation	Emmanuel Brempong Asiedu, Simon Kornblith, Ting Chen	2022	arxiv 2205.11423
Three Ways to Improve Semantic Segmentation with Self-Supervised Depth Estimation	Lukas Hoyer, Dengxin Dai, Yuhua Chen	2020	arxiv 2012.10782
Random Forest with Learned Representations for Semantic Segmentation