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Learning Multi-level Region Consistency with Dense Multi-label Networks
  for Semantic Segmentation

Learning Multi-level Region Consistency with Dense Multi-label Networks for Semantic Segmentation

International Joint Conference on Artificial Intelligence (IJCAI), 2017
25 January 2017
T. Shen
Guosheng Lin
Chunhua Shen
Ian Reid
    SSeg
ArXiv (abs)PDFHTML

Papers citing "Learning Multi-level Region Consistency with Dense Multi-label Networks for Semantic Segmentation"

4 / 4 papers shown
Title
Multi-Label Adversarial Perturbations
Multi-Label Adversarial Perturbations
Qingquan Song
Haifeng Jin
Xiao Huang
Helen Zhou
AAML
91
40
0
02 Jan 2019
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
170
42
0
17 Apr 2018
Decoupled Spatial Neural Attention for Weakly Supervised Semantic
  Segmentation
Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation
Tianyi Zhang
Guosheng Lin
Jianfei Cai
T. Shen
Chunhua Shen
Alex C. Kot
118
80
0
07 Mar 2018
Weakly Supervised Semantic Segmentation Based on Web Image
  Co-segmentation
Weakly Supervised Semantic Segmentation Based on Web Image Co-segmentation
T. Shen
Guosheng Lin
Lingqiao Liu
Chunhua Shen
Ian Reid
SSeg
142
16
0
25 May 2017
1