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Mixed context networks for semantic segmentation

Mixed context networks for semantic segmentation

19 October 2016
Haiming Sun
Di Xie
Shiliang Pu
    SSeg
ArXiv (abs)PDFHTML

Papers citing "Mixed context networks for semantic segmentation"

6 / 6 papers shown
Title
Your Image is My Video: Reshaping the Receptive Field via Image-To-Video
  Differentiable AutoAugmentation and Fusion
Your Image is My Video: Reshaping the Receptive Field via Image-To-Video Differentiable AutoAugmentation and FusionComputer Vision and Pattern Recognition (CVPR), 2024
S. Casarin
C. Ugwu
Sergio Escalera
Oswald Lanz
225
0
0
22 Mar 2024
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and
  Beyond
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and BeyondNeural Information Processing Systems (NeurIPS), 2021
Đ.Khuê Lê-Huu
Alahari Karteek
224
13
0
27 Oct 2021
Vortex Pooling: Improving Context Representation in Semantic
  Segmentation
Vortex Pooling: Improving Context Representation in Semantic Segmentation
Chen-Wei Xie
Hong-Yu Zhou
Jianxin Wu
SSeg
126
42
0
17 Apr 2018
Per-Pixel Feedback for improving Semantic Segmentation
Per-Pixel Feedback for improving Semantic Segmentation
Aditya Ganeshan
SSeg
84
0
0
07 Dec 2017
Rethinking Atrous Convolution for Semantic Image Segmentation
Rethinking Atrous Convolution for Semantic Image Segmentation
Liang-Chieh Chen
George Papandreou
Florian Schroff
Hartwig Adam
SSeg
611
9,353
0
17 Jun 2017
Understanding Convolution for Semantic Segmentation
Understanding Convolution for Semantic SegmentationIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2017
Panqu Wang
Pengfei Chen
Ye Yuan
Ding Liu
Zehua Huang
Xiaodi Hou
G. Cottrell
SSeg
232
1,823
0
27 Feb 2017
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