Xingchao Peng | DeepAI

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Featured Co-authors

Kate Saenko
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Yizhe Zhu
27 publications
Dequan Wang
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Kuniaki Saito
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Yichen Li
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Ximeng Sun
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Qinxun Bai
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∙ 08/13/2020

Network Architecture Search for Domain Adaptation

Deep networks have been used to learn transferable representations for d...

22 Yichen Li, et al. ∙

∙ 07/17/2020

Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation

Conventional unsupervised domain adaptation (UDA) studies the knowledge ...

17 Xingchao Peng, et al. ∙

∙ 12/10/2019

Learning Domain Adaptive Features with Unlabeled Domain Bridges

Conventional cross-domain image-to-image translation or unsupervised dom...

0 Yichen Li, et al. ∙

∙ 11/05/2019

Federated Adversarial Domain Adaptation

Federated learning improves data privacy and efficiency in machine learn...

17 Xingchao Peng, et al. ∙

∙ 10/23/2019

Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment

Unsupervised knowledge transfer has a great potential to improve the gen...

16 Shuhan Tan, et al. ∙

∙ 04/28/2019

Domain Agnostic Learning with Disentangled Representations

Unsupervised model transfer has the potential to greatly improve the gen...

18 Xingchao Peng, et al. ∙

∙ 12/04/2018

Moment Matching for Multi-Source Domain Adaptation

Conventional unsupervised domain adaptation (UDA) assumes that training ...

10 Xingchao Peng, et al. ∙

∙ 06/26/2018

Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation

Unsupervised transfer of object recognition models from synthetic to rea...

4 Xingchao Peng, et al. ∙

∙ 10/18/2017

VisDA: The Visual Domain Adaptation Challenge

We present the 2017 Visual Domain Adaptation (VisDA) dataset and challen...

0 Xingchao Peng, et al. ∙

∙ 01/19/2017

Synthetic to Real Adaptation with Generative Correlation Alignment Networks

Synthetic images rendered from 3D CAD models are useful for augmenting t...

0 Xingchao Peng, et al. ∙

∙ 09/14/2016

Combining Texture and Shape Cues for Object Recognition With Minimal Supervision

We present a novel approach to object classification and detection which...

0 Xingchao Peng, et al. ∙

∙ 05/21/2016

Fine-to-coarse Knowledge Transfer For Low-Res Image Classification

We address the difficult problem of distinguishing fine-grained object c...

0 Xingchao Peng, et al. ∙

∙ 04/09/2015

What Do Deep CNNs Learn About Objects?

Deep convolutional neural networks learn extremely powerful image repres...

0 Xingchao Peng, et al. ∙

∙ 12/22/2014

Learning Deep Object Detectors from 3D Models

Crowdsourced 3D CAD models are becoming easily accessible online, and ca...

0 Xingchao Peng, et al. ∙

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