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
Fusion of Multispectral Data Through Illumination-aware Deep Neural Networks for Pedestrian Detection	Dayan Guan, Yanpeng Cao, Jun Liang	2018	arxiv 1802.09972
Deep learning and its application to medical image segmentation	Holger R. Roth, Chen Shen, Hirohisa Oda	2018	arxiv 1803.08691
Learning Pixel-wise Labeling from the Internet without Human Interaction	Yun Liu, Yujun Shi, JiaWang Bian	2018	arxiv 1805.07548
Pixelated Semantic Colorization	Jiaojiao Zhao, Jungong Han, Ling Shao	2019	arxiv 1901.10889
Building Change Detection for Remote Sensing Images Using a Dual Task Constrained Deep Siamese Convolutional Network Model	Yi Liu, Chao Pang, Zongqian Zhan	2019	arxiv 1909.07726
Quadtree Generating Networks: Efficient Hierarchical Scene Parsing with Sparse Convolutions	Kashyap Chitta, Jose M. Alvarez, Martial Hebert	2019	arxiv 1907.11821
PointRend: Image Segmentation as Rendering	Alexander Kirillov, Yuxin Wu, Kaiming He	2019	arxiv 1912.08193
Deep High-Resolution Representation Learning for Visual Recognition	Jingdong Wang, Ke Sun, Tianheng Cheng	2019	arxiv 1908.07919
Phase Consistent Ecological Domain Adaptation	Yanchao Yang, Dong Lao, Ganesh Sundaramoorthi	2020	arxiv 2004.04923
Segmentation of Surgical Instruments for Minimally-Invasive Robot-Assisted Procedures Using Generative Deep Neural Networks	Iñigo Azqueta-Gavaldon, Florian Fröhlich, Klaus Strobl	2020	arxiv 2006.03486