XingChao Peng
XingChao Peng
確認したメール アドレス: bu.edu - 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
2792015
Moment matching for multi-source domain adaptation
X Peng, Q Bai, X Xia, Z Huang, K Saenko, B Wang
Proceedings of the IEEE International Conference on Computer Vision, 1406-1415, 2019
1372019
Visda: The visual domain adaptation challenge
X Peng, B Usman, N Kaushik, J Hoffman, D Wang, K Saenko
arXiv preprint arXiv:1710.06924, 2017
1002017
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
802015
Synthetic to real adaptation with generative correlation alignment networks
X Peng, K Saenko
arXiv preprint arXiv:1701.05524, 2017
532017
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
492014
Domain agnostic learning with disentangled representations
X Peng, Z Huang, X Sun, K Saenko
arXiv preprint arXiv:1904.12347, 2019
432019
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
372016
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
352018
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
222018
Federated adversarial domain adaptation
X Peng, Z Huang, Y Zhu, K Saenko
arXiv preprint arXiv:1911.02054, 2019
122019
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
112015
Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment
S Tan, X Peng, K Saenko
arXiv preprint arXiv:1910.10320, 2019
42019
Combining texture and shape cues for object recognition with minimal supervision
X Peng, K Saenko
Asian Conference on Computer Vision, 256-272, 2016
42016
What Do Deep CNNs Learn About Objects?
X Peng, B Sun, K Ali, K Saenko
arXiv preprint arXiv:1504.02485, 2015
32015
Learning Domain Adaptive Features with Unlabeled Domain Bridges
Y Li, X Peng
arXiv preprint arXiv:1912.05004, 2019
22019
Network architecture search for domain adaptation
Y Li, X Peng
arXiv preprint arXiv:2008.05706, 2020
12020
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
12018
Ground2sky label transfer for fine-grained aerial car recognition
B Sun, X Peng, XY Stella, K Saenko
2017 IEEE International Conference on Image Processing (ICIP), 360-364, 2017
12017
Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation
X Peng, Y Li, K Saenko
arXiv preprint arXiv:2007.09257, 2020
2020
現在システムで処理を実行できません。しばらくしてからもう一度お試しください。
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