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We present the 2017 Visual Domain Adaptation (VisDA) dataset and challenge, a large-scale testbed for unsupervised domain adaptation across visual domains.
A database for handwritten text recognition research
J. J. Hull · 1994
Earlier work this paper cites.
Columbia object image library (coil-20)
S. A. Nene, S. K. Nayar, H. Murase, et al · 1996
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner · 1998
Earlier work this paper cites.
The cmu pose, illumination, and expression (pie) database
T. Sim, S. Baker, and M. Bsat · 2002
Earlier work this paper cites.
On visual similarity based 3d model retrieval
D.-Y. Chen, X.-P. Tian, Y.-T. Shen, and M. Ouhyoung · 2003
Earlier work this paper cites.
Dataset Shift in Machine Learning
J. Quionero-Candela, M. Sugiyama, A. Schwaighofer, and N. D. Lawrence · 2009
Earlier work this paper cites.
Exploiting weakly-labeled web images to improve object classification: a domain adaptation approach
A. Bergamo and L. Torresani · 2010
Earlier work this paper cites.
Visual event recognition in videos by learning from web data
L. Duan, D. Xu, I. Tsang, and J. Luo · 2010
Earlier work this paper cites.
Understanding the difficulty of training deep feedforward neural networks
X. Glorot and Y. Bengio · 2010
Earlier work this paper cites.
Adapting visual category models to new domains
K. Saenko, B. Kulis, M. Fritz, and T. Darrell · 2010
Earlier work this paper cites.
Shrec’10 track: Generic 3d warehouse
T. P. Vanamali, A. Godil, H. Dutagaci, T. Furuya, Z. Lian, and R. Ohbuchi · 2010
Earlier work this paper cites.
Reading digits in natural images with unsupervised feature learning
Y. Netzer, T. Wang, A. Coates, A. Bissacco, B. Wu, and A. Y. Ng · 2011
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.
A large-scale shape benchmark for 3d object retrieval: Toyohashi shape benchmark
A. Tatsuma, H. Koyanagi, and M. Aono · 2012
Earlier work this paper cites.
Caffe: An open source convolutional architecture for fast feature embedding
Y. Jia · 2013
Earlier work this paper cites.
Parsing IKEA Objects: Fine Pose Estimation
J. J. Lim, H. Pirsiavash, and A. Torralba · 2013
Earlier work this paper cites.
Equivalence of distance-based and rkhs-based statistics in hypothesis testing
D. Sejdinovic, B. Sriperumbudur, A. Gretton, and K. Fukumizu · 2013
Earlier work this paper cites.
Unsupervised domain adaptation by backpropagation
Y. Ganin and V. Lempitsky · 2014
Earlier work this paper cites.
Microsoft COCO: common objects in context
T. Lin, M. Maire, S. J. Belongie, L. D. Bourdev, R. B. Girshick, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
Cited alongside, same era.
From virtual to reality: Fast adaptation of virtual object detectors to real domains
B. Sun and K. Saenko · 2014
Cited alongside, same era.
A testbed for cross-dataset analysis
T. Tommasi, T. Tuytelaars, and B. Caputo · 2014
Cited alongside, same era.
Virtual and real world adaptation for pedestrian detection
D. Vazquez, A. M. Lopez, J. Marin, D. Ponsa, and D. Geronimo · 2014
Cited alongside, same era.
Beyond pascal: A benchmark for 3d object detection in the wild
Y. Xiang, R. Mottaghi, and S. Savarese · 2014
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
Later among the works it cites.
Perceptual losses for real-time style transfer and super-resolution
J. Johnson, A. Alahi, and F. Li · 2016
Later among the works it cites.
Temporal ensembling for semi-supervised learning
S. Laine and T. Aila · 2016
Later among the works it cites.
Precomputed real-time texture synthesis with markovian generative adversarial networks
C. Li and M. Wand · 2016
Later among the works it cites.
Playing for data: Ground truth from computer games
S. R. Richter, V. Vineet, S. Roth, and V. Koltun · 2016
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Cited alongside, same era.
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L. A. Gatys, A. S. Ecker, and M. Bethge · 2015
Cited alongside, same era.
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Cited alongside, same era.
Learning deep object detectors from 3d models
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ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
Cited alongside, same era.
Render for cnn: Viewpoint estimation in images using cnns trained with rendered 3d model views
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Cited alongside, same era.
Return of frustratingly easy domain adaptation
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Cited alongside, same era.
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The SYNTHIA Dataset: A large collection of synthetic images for semantic segmentation of urban scenes
G. Ros, L. Sellart, J. Materzynska, D. Vazquez, and A. Lopez · 2016
Later among the works it cites.
Deep CORAL: correlation alignment for deep domain adaptation
B. Sun and K. Saenko · 2016
Later among the works it cites.
Texture networks: Feed-forward synthesis of textures and stylized images
D. Ulyanov, V. Lebedev, A. Vedaldi, and V. S. Lempitsky · 2016
Later among the works it cites.
Objectnet3d: A large scale database for 3d object recognition
Y. Xiang, W. Kim, W. Chen, J. Ji, C. Choy, H. Su, R. Mottaghi, L. Guibas, and S. Savarese · 2016
Later among the works it cites.
Aggregated residual transformations for deep neural networks
S. Xie, R. Girshick, P. Dollár, Z. Tu, and K. He · 2016
Later among the works it cites.
Autodial: Automatic domain alignment layers
F. M. Carlucci, L. Porzi, B. Caputo, E. Ricci, and S. R. Bulò · 2017
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Domain adaptation for visual applications: A comprehensive survey
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M. Long, H. Zhu, J. Wang, and M. I. Jordan · 2017
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