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
Analysing the effectiveness of a generative model for semi-supervised medical image segmentation	Margherita Rosnati, Fabio De Sousa Ribeiro, Miguel Monteiro	2022	arxiv 2211.01886
Incomplete Multimodal Learning for Remote Sensing Data Fusion	Yuxing Chen, Maofan Zhao, Lorenzo Bruzzone	2023	arxiv 2304.11381
Detecting Novelties with Empty Classes	Svenja Uhlemeyer, Julian Lienen, Eyke Hüllermeier	2023	arxiv 2305.00983
Universal Adaptive Data Augmentation	Xiaogang Xu, Hengshuang Zhao	2022	arxiv 2207.06658
DMNR: Unsupervised De-noising of Point Clouds Corrupted by Airborne Particles	Chu Chen, Yanqi Ma, Bingcheng Dong	2023	arxiv 2305.05991
Implicit Integration of Superpixel Segmentation into Fully Convolutional Networks	Teppei Suzuki	2021	arxiv 2103.03435
Understanding Gaussian Attention Bias of Vision Transformers Using Effective Receptive Fields	Bum Jun Kim, Hyeyeon Choi, Hyeonah Jang	2023	arxiv 2305.04722
Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation	Zhiqiang Shen, Peng Cao, Hua Yang	2023	arxiv 2301.04465
Rethinking Local Perception in Lightweight Vision Transformer	Qihang Fan, Huaibo Huang, Jiyang Guan	2023	arxiv 2303.17803
Optimizing Vision Transformers for Medical Image Segmentation	Qianying Liu, Chaitanya Kaul, Jun Wang	2022	arxiv 2210.08066