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
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond	\DJ.Khuê Lê-Huu, Karteek Alahari	2021	arxiv 2110.14759
Instance-sensitive Fully Convolutional Networks	Jifeng Dai, Kaiming He, Yi Li	2016	arxiv 1603.08678
Compact Bilinear Pooling	Yang Gao, Oscar Beijbom, Ning Zhang	2015	arxiv 1511.06062
Object Detection from Video Tubelets with Convolutional Neural Networks	Kai Kang, Wanli Ouyang, Hongsheng Li	2016	arxiv 1604.04053
Dilated Residual Networks	Fisher Yu, Vladlen Koltun, Thomas Funkhouser	2017	arxiv 1705.09914
Effective Use of Dilated Convolutions for Segmenting Small Object Instances in Remote Sensing Imagery	Ryuhei Hamaguchi, Aito Fujita, Keisuke Nemoto	2017	arxiv 1709.00179
Convolutional Neural Fabrics	Shreyas Saxena, Jakob Verbeek	2016	arxiv 1606.02492
The Relative Performance of Ensemble Methods with Deep Convolutional Neural Networks for Image Classification	Cheng Ju, Aurélien Bibaut, Mark J. van der Laan	2017	arxiv 1704.01664
Loss Max-Pooling for Semantic Image Segmentation	Samuel Rota Bulò, Gerhard Neuhold, Peter Kontschieder	2017	arxiv 1704.02966
Salient Object Detection with Semantic Priors	Tam V. Nguyen, Luoqi Liu	2017	arxiv 1705.08207
Semantic 3D Occupancy Mapping through Efficient High Order CRFs