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@@ -110,12 +110,13 @@ Please feel free to [pull requests](https://github.com/kjw0612/awesome-deep-visi
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### Semantic Segmentation
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### Semantic Segmentation
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(from Jifeng Dai, Kaiming He, Jian Sun, BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation, arXiv:1503.01640.)
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(from Jifeng Dai, Kaiming He, Jian Sun, BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation, arXiv:1503.01640.)
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+ * PASCAL VOC2012 Challenge
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-(from PASCAL VOC 2012 [leaderboards](http://host.robots.ox.ac.uk:8080/leaderboard/displaylb.php?challengeid=11&compid=6))
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+(from PASCAL VOC2012 [leaderboards](http://host.robots.ox.ac.uk:8080/leaderboard/displaylb.php?challengeid=11&compid=6))
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* Adelaide
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* Adelaide
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* Guosheng Lin, Chunhua Shen, Ian Reid, Anton van dan Hengel, Efficient piecewise training of deep structured models for semantic segmentation, arXiv:1504.01013. [[Paper]](http://arxiv.org/pdf/1504.01013) (1st ranked in VOC2012)
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* Guosheng Lin, Chunhua Shen, Ian Reid, Anton van dan Hengel, Efficient piecewise training of deep structured models for semantic segmentation, arXiv:1504.01013. [[Paper]](http://arxiv.org/pdf/1504.01013) (1st ranked in VOC2012)
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- * Guosheng Lin, Chunhua Shen, Ian Reid, Anton van den Hengel, Deeply Learning the Messages in Message Passing Inference, arXiv:1506.02108. [[Paper]](http://arxiv.org/pdf/1506.02108) (4th ranked in VOC2012)
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+ * Guosheng Lin, Chunhua Shen, Ian Reid, Anton van den Hengel, Deeply Learning the Messages in Message Passing Inference, arXiv:1508.02108. [[Paper]](http://arxiv.org/pdf/1506.02108) (4th ranked in VOC2012)
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* BoxSup [[Paper]](http://arxiv.org/pdf/1503.01640)
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* BoxSup [[Paper]](http://arxiv.org/pdf/1503.01640)
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* Jifeng Dai, Kaiming He, Jian Sun, BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation, arXiv:1503.01640. (2nd ranked in VOC2012)
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* Jifeng Dai, Kaiming He, Jian Sun, BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation, arXiv:1503.01640. (2nd ranked in VOC2012)
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* Conditional Random Fields as Recurrent Neural Networks [[Paper]](http://arxiv.org/pdf/1502.03240)
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* Conditional Random Fields as Recurrent Neural Networks [[Paper]](http://arxiv.org/pdf/1502.03240)
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@@ -125,6 +126,7 @@ Please feel free to [pull requests](https://github.com/kjw0612/awesome-deep-visi
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* POSTECH
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* POSTECH
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* Hyeonwoo Noh, Seunghoon Hong, Bohyung Han, Learning Deconvolution Network for Semantic Segmentation, arXiv:1505.04366. [[Paper]](http://arxiv.org/pdf/1505.04366) (6th ranked in VOC2012)
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* Hyeonwoo Noh, Seunghoon Hong, Bohyung Han, Learning Deconvolution Network for Semantic Segmentation, arXiv:1505.04366. [[Paper]](http://arxiv.org/pdf/1505.04366) (6th ranked in VOC2012)
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* Seunghoon Hong, Hyeonwoo Noh, Bohyung Han, Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation, arXiv:1506.04924. [[Paper]](http://arxiv.org/pdf/1506.04924)
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* Seunghoon Hong, Hyeonwoo Noh, Bohyung Han, Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation, arXiv:1506.04924. [[Paper]](http://arxiv.org/pdf/1506.04924)
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+
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* Joint Calibration [[Paper]](http://arxiv.org/pdf/1507.01581)
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* Joint Calibration [[Paper]](http://arxiv.org/pdf/1507.01581)
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* Holger Caesar, Jasper Uijlings, Vittorio Ferrari, Joint Calibration for Semantic Segmentation, arXiv:1507.01581.
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* Holger Caesar, Jasper Uijlings, Vittorio Ferrari, Joint Calibration for Semantic Segmentation, arXiv:1507.01581.
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* Fully Convolutional Networks for Semantic Segmentation [[Paper-CVPR15]](http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Long_Fully_Convolutional_Networks_2015_CVPR_paper.pdf) [[Paper-arXiv15]](http://arxiv.org/pdf/1411.4038)
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* Fully Convolutional Networks for Semantic Segmentation [[Paper-CVPR15]](http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Long_Fully_Convolutional_Networks_2015_CVPR_paper.pdf) [[Paper-arXiv15]](http://arxiv.org/pdf/1411.4038)
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