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Fully convolutional models for dense prediction have proven successful for a wide range of visual tasks.
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Geodesic flow kernel for unsupervised domain adaptation
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Learning hierarchical features for scene labeling
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Generative adversarial nets
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Simultaneous detection and segmentation
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Semantic image segmentation with deep convolutional nets and fully connected crfs
L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2015
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Unsupervised domain adaptation by backpropagation
Y. Ganin and V. Lempitsky · 2015
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Detector discovery in the wild: Joint multiple instance and representation learning
J. Hoffman, D. Pathak, T. Darrell, and K. Saenko · 2015
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Decoupled deep neural network for semi-supervised semantic segmentation
S. Hong, H. Noh, and B. Han · 2015
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J. Long, E. Shelhamer, and T. Darrell · 2015
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M. Long, Y. Cao, J. Wang, and M. Jordan · 2015
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Weakly-and semi-supervised learning of a deep convolutional network for semantic image segmentation
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Constrained convolutional neural networks for weakly supervised segmentation
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The cityscapes dataset for semantic urban scene understanding
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Instance-aware semantic segmentation via multi-task network cascades
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Domain-adversarial training of neural networks
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Large scale visual recognition through adaptation using joint representation and multiple instance learning
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Learning transferrable knowledge for semantic segmentation with deep convolutional neural network
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Fully convolutional multi-class multiple instance learning
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From image-level to pixel-level labeling with convolutional networks
P. O. Pinheiro and R. Collobert · 2015
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
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Simultaneous deep transfer across domains and tasks
E. Tzeng, J. Hoffman, T. Darrell, and K. Saenko · 2015
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Conditional random fields as recurrent neural networks
S. Zheng, S. Jayasumana, B. Romera-Paredes, V. Vineet, Z. Su, D. Du, C. Huang, and P. H. Torr · 2015
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S. Hong, J. Oh, B. Han, and H. Lee · 2016
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Unsupervised domain adaptation with residual transfer networks
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Playing for data: Ground truth from computer games
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The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes
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