XingChao Peng
XingChao Peng
確認したメール アドレス: microsoft.com - ホームページ
タイトル
引用先
引用先
Learning deep object detectors from 3d models
X Peng, B Sun, K Ali, K Saenko
Proceedings of the IEEE International Conference on Computer Vision, 1278-1286, 2015
3222015
Moment matching for multi-source domain adaptation
X Peng, Q Bai, X Xia, Z Huang, K Saenko, B Wang
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
2892019
Visda: The visual domain adaptation challenge
X Peng, B Usman, N Kaushik, J Hoffman, D Wang, K Saenko
arXiv preprint arXiv:1710.06924, 2017
1782017
Towards adapting deep visuomotor representations from simulated to real environments
E Tzeng, C Devin, J Hoffman, C Finn, X Peng, S Levine, K Saenko, ...
arXiv preprint arXiv:1511.07111 2 (3), 2015
862015
Domain agnostic learning with disentangled representations
X Peng, Z Huang, X Sun, K Saenko
International Conference on Machine Learning, 5102-5112, 2019
772019
Synthetic to real adaptation with generative correlation alignment networks
X Peng, K Saenko
arXiv preprint arXiv:1701.05524, 2017
702017
Exploring invariances in deep convolutional neural networks using synthetic images
X Peng, B Sun, K Ali, K Saenko
CoRR, abs/1412.7122 2 (4), 2014
582014
Fine-to-coarse Knowledge Transfer For Low-Res Image Classification
X Peng, J Hoffman, SX Yu, K Saenko
IEEE International Conference on Image Processing 2016, 2016
472016
Visda: A synthetic-to-real benchmark for visual domain adaptation
X Peng, B Usman, N Kaushik, D Wang, J Hoffman, K Saenko
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
462018
Federated adversarial domain adaptation
X Peng, Z Huang, Y Zhu, K Saenko
arXiv preprint arXiv:1911.02054, 2019
452019
Syn2real: A new benchmark forsynthetic-to-real visual domain adaptation
X Peng, B Usman, K Saito, N Kaushik, J Hoffman, K Saenko
arXiv preprint arXiv:1806.09755, 2018
422018
Generating large scale image datasets from 3D CAD models
B Sun, X Peng, K Saenko
CVPR 2015 Workshop on The Future of Datasets in Vision, 2015
132015
Generalized domain adaptation with covariate and label shift co-alignment
S Tan, X Peng, K Saenko
52019
Combining texture and shape cues for object recognition with minimal supervision
X Peng, K Saenko
Asian Conference on Computer Vision, 256-272, 2016
52016
Domain2vec: Domain embedding for unsupervised domain adaptation
X Peng, Y Li, K Saenko
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
42020
Class-imbalanced domain adaptation: an empirical odyssey
S Tan, X Peng, K Saenko
European Conference on Computer Vision, 585-602, 2020
32020
What Do Deep CNNs Learn About Objects?
X Peng, B Sun, K Ali, K Saenko
arXiv preprint arXiv:1504.02485, 2015
32015
Adapting control policies from simulation to reality using a pairwise loss
U Viereck, X Peng, K Saenko, R Platt
International Symposium on Experimental Robotics, 256-266, 2018
22018
Network architecture search for domain adaptation
Y Li, X Peng
arXiv preprint arXiv:2008.05706, 2020
12020
Learning domain adaptive features with unlabeled domain bridges
Y Li, X Peng
arXiv preprint arXiv:1912.05004, 2019
12019
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