Papers

2018 Papers

IJCV

[arxiv 1801.06397] What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? [PDF] [notes]

Nikolaus Mayer, Eddy Ilg, Philipp Fischer, Caner Hazirbas, Daniel Cremers, Alexey Dosovitskiy, Thomas Brox

read 17/04/2018

2017 Papers

ICCV

[arxiv 1612.05424] Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks [PDF] [notes]

Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan

read 03/08/2017

NIPS

[nips 17.6612] Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks [PDF] [notes]

Jian Zhao, Lin Xiong, Karlekar Jayashree, Jianshu Li, Fang Zhao, Zhecan Wang

read 04/25/2017

Arxiv

[arxiv 1710.10710] On Pre-Trained Image Features and Synthetic Images for Deep Learning [PDF] [notes]

Stefan Hinterstoisser, Vincent Lepetit, Paul Wohlhart, Kurt Konolige

read 04/25/2017

2016 Papers

GMDL (Workshop at ECCV)

[arxiv 1603.08152] How useful is photo-realistic rendering for visual learning? [PDF] [notes]

Yair Movshovitz-Attias, Takeo Kanade, Yaser Sheikh

read 17/04/2018

2015 Papers

ICML

[arxiv 1409.7495] Unsupervised Domain Adaptation by Backpropagation [PDF] [notes]

Yaroslav Ganin, Victor Lempitsky

read 03/08/2017