Fetching the paper…
Reading the bibliography…
In this paper, we present an adversarial unsupervised domain adaptation framework for object detection.
Histograms of oriented gradients for human detection
N. Dalal and B. Triggs · 2005
Earlier work this paper cites.
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.
The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2012
Earlier work this paper cites.
Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
Earlier work this paper cites.
Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
Earlier work this paper cites.
Microsoft coco: Common objects in context
T. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
Earlier work this paper cites.
Unsupervised domain adaptation by backpropagation
Y. Ganin and V. Lempitsky · 2014
Earlier work this paper cites.
Deep domain confusion: Maximizing for domain invariance
E. Tzeng, J. Hoffman, N. Zhang, K. Saenko, and T. Darrell · 2014
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.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Earlier work this paper cites.
Fast r-cnn
R. Girshick · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
Cited alongside, same era.
Spatial pyramid pooling in deep convolutional networks for visual recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2015
Cited alongside, same era.
Learning transferable features with deep adaptation networks
M. Long, Y. Cao, J. Wang, and M. I. Jordan · 2015
Cited alongside, same era.
You only look once: Unified, real-time object detection
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi · 2016
Cited alongside, same era.
Ssd: Single shot multibox detector
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C. Fu, and A. C. Berg · 2016
Cited alongside, same era.
Large scale semi-supervised object detection using visual and semantic knowledge transfer
M. Arjovsky, S. Chintala, and L. Bottou · 2017
Later among the works it cites.
Conditional image synthesis with auxiliary classifier gans
A. Odena, C. Olah, and J. Shlens · 2017
Later among the works it cites.
Unpaired image-to-image translation using cycle-consistent adversarial networks
J. Zhu, T. Park, P. Isola, and A. Efros · 2017
Later among the works it cites.
Cross-domain weakly-supervised object detection through progressive domain adaptation
N. Inoue, R. Furuta, T. Yamasaki, and K. Aizawa · 2018
Later among the works it cites.
Strong-weak distribution alignment for adaptive object detection
Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada, and Kate Saenko · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Y. Tang, J. Wang, B. Gao, E. Dellandréa, R. Gaizauskas, and L. Chen · 2016
Cited alongside, same era.
Weakly supervised deep detection networks
H. Bilen and A. Vedaldi · 2016
Cited alongside, same era.
Perceptual losses for real-time style transfer and super-resolution
J. Johnson, A. Alahi, and F. Li · 2016
Cited alongside, same era.
The cityscapes dataset for semantic urban scene understanding
M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele · 2016
Cited alongside, same era.
Mask r-cnn
K. He, G. Gkioxari, P. Dollár, and R. Girshick · 2017
Cited alongside, same era.
Adversarial discriminative domain adaptation
E. Tzeng, J. Hoffman, K. Saenko, and T. Darrell · 2017
Cited alongside, same era.
Domain adaptive faster r-cnn for object detection in the wild
Y. Chen, W. Li, C. Sakaridis, D. Dai, and L. Van Gool · 2018
Later among the works it cites.
Learning from synthetic data: Addressing domain shift for semantic segmentation
S. Sankaranarayanan, Y. Balaji, A. Jain, S. Nam Lim, and R. Chellappa · 2018
Later among the works it cites.
Spectral normalization for generative adversarial networks
T. Miyato, T. Kataoka, M. Koyama, and Y. Yoshida · 2018
Later among the works it cites.
Semantic foggy scene understanding with synthetic data
C. Sakaridis, D. Dai, and L. Van Gool · 2018
Later among the works it cites.
Y. Balaji, R. Chellappa, and S. Feizi · 2019
Closest in time.