Fetching the paper…
Reading the bibliography…
Convolutional neural network-based approaches for semantic segmentation rely on supervision with pixel-level ground truth, but may not generalize well to unseen image domains.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
Earlier work this paper cites.
Are we ready for autonomous driving? the kitti vision benchmark suite
A. Geiger, P. Lenz, and R. Urtasun · 2012
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Earlier work this paper cites.
Rectifier nonlinearities improve neural network acoustic models
A. L. Maas, A. Y. Hannun, and A. Y. Ng · 2013
Earlier work this paper cites.
Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
Earlier work this paper cites.
Boxsup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation
J. Dai, K. He, and J. Sun · 2015
Earlier work this paper cites.
Unsupervised domain adaptation by backpropagation
Y. Ganin and V. Lempitsky · 2015
Earlier work this paper cites.
Decoupled deep neural network for semi-supervised semantic segmentation
S. Hong, H. Noh, and B. Han · 2015
Earlier work this paper cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
Earlier work this paper cites.
Deeply-supervised nets
C. Lee, S. Xie, P. W. Gallagher, Z. Zhang, and Z. Tu · 2015
Earlier work this paper cites.
Semantic image segmentation via deep parsing network
Z. Liu, X. Li, P. Luo, C. C. Loy, and X. Tang · 2015
Earlier work this paper cites.
Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
Earlier work this paper cites.
Learning transferable features with deep adaptation networks
M. Long, Y. Cao, J. Wang, and M. Jordan · 2015
Earlier work this paper cites.
Weakly-and semi-supervised learning of a dcnn for semantic image segmentation
G. Papandreou, L.-C. Chen, K. Murphy, and A. L. Yuille · 2015
Earlier work this paper cites.
Constrained convolutional neural networks for weakly supervised segmentation
D. Pathak, P. Krahenbuhl, and T. Darrell · 2015
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
Cited alongside, same era.
Simultaneous deep transfer across domains and tasks
E. Tzeng, J. Hoffman, T. Darrell, and K. Saenko · 2015
Cited alongside, same era.
Conditional random fields as recurrent neural networks
S. Zheng, S. Jayasumana, B. Romera-Paredes, V. Vineet, Z. Su, D. Du, C. Huang, and P. Torr · 2015
Cited alongside, same era.
L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2016
Cited alongside, same era.
Multi-scale context aggregation by dilated convolutions
F. Yu and V. Koltun · 2016
Later among the works it cites.
Unsupervised pixel-level domain adaptation with generative adversarial networks
K. Bousmalis, N. Silberman, D. Dohan, D. Erhan, and D. Krishnan · 2017
Later among the works it cites.
No more discrimination: Cross city adaptation of road scene segmenters
Y.-H. Chen, W.-Y. Chen, Y.-T. Chen, B.-C. Tsai, Y.-C. F. Wang, and M. Sun · 2017
Later among the works it cites.
Cycada: Cycle-consistent adversarial domain adaptation
J. Hoffman, E. Tzeng, T. Park, J.-Y. Zhu, P. Isola, K. Saenko, A. A. Efros, and T. Darrell · 2017
Later among the works it cites.
Scene parsing with global context embedding
W.-C. Hung, Y.-H. Tsai, X. Shen, Z. Lin, K. Sunkavalli, X. Lu, and M.-H. Yang · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele · 2016
Cited alongside, same era.
Domain-adversarial training of neural networks
Y. Ganin, E. Ustinova, H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, M. Marchand, and V. Lempitsky · 2016
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Fcns in the wild: Pixel-level adversarial and constraint-based adaptation
J. Hoffman, D. Wang, F. Yu, and T. Darrell · 2016
Cited alongside, same era.
Efficient piecewise training of deep structured models for semantic segmentation
G. Lin, C. Shen, A. van dan Hengel, and I. Reid · 2016
Cited alongside, same era.
Coupled generative adversarial networks
M.-Y. Liu and O. Tuzel · 2016
Cited alongside, same era.
Unsupervised domain adaptation with residual transfer networks
M. Long, H. Zhu, J. Wang, and M. I. Jordan · 2016
Cited alongside, same era.
A. Khoreva, R. Benenson, J. Hosang, M. Hein, and B. Schiele · 2017
Later among the works it cites.
Least squares generative adversarial networks
X. Mao, Q. Li, H. Xie, R. Y. Lau, Z. Wang, and S. Paul Smolley · 2017
Later among the works it cites.
Unsupervised domain adaptation for face recognition in unlabeled videos
K. Sohn, S. Liu, G. Zhong, X. Yu, M.-H. Yang, and M. Chandraker · 2017
Later among the works it cites.
Deep image harmonization
Y.-H. Tsai, X. Shen, Z. Lin, K. Sunkavalli, X. Lu, and M.-H. Yang · 2017
Later among the works it cites.
Adversarial discriminative domain adaptation
E. Tzeng, J. Hoffman, K. Saenko, and T. Darrell · 2017
Later among the works it cites.
Curriculum domain adaptation for semantic segmentation of urban scenes
Y. Zhang, P. David, and B. Gong · 2017
Later among the works it cites.
Pyramid scene parsing network
H. Zhao, J. Shi, X. Qi, X. Wang, and J. Jia · 2017
Later among the works it cites.
Unpaired image-to-image translation using cycle-consistent adversarial networks
J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros · 2017
Later among the works it cites.
Synscapes: A photorealistic synthetic dataset for street scene parsing
M. Wrenninge and J. Unger · 2018
Closest in time.