1. 

   Joint Pixel and Feature-Level Domain Adaptation for Recognition in the Wild

   Luan Tran, Kihyuk Sohn, Xiang Yu, Xiaoming Liu, Manmohan Chandraker

   Recent developments in deep domain adaptation have allowed knowledge transfer from a labeled source domain to an unlabeled target domain at the level of intermediate features and input pixels. We propose that advantages may be derived by jointly investigating the two, in the form of different level insights that lead ...

   Continue reading

   Keywords: Domain Adaptation

2. 

   Feature Transfer Learning for Deep Face Recognition with Long-Tail Data

   Xi Yin, Xiang Yu, Kihyuk Sohn, Xiaoming Liu, Manmohan Chandraker

   Real-world face recognition datasets exhibit long-tail characteristics, which results in biased classifiers in conventionally-trained deep neural networks, or insufficient data when long-tail classes are ignored. In this paper, we propose to handle long-tail classes in the training of a face recognition engine by augmenting their feature space under a center-based ...

   Continue reading

   Keywords: Face Recognition, Biometrics

3. 

   Towards Large-Pose Face Frontalization in the Wild

   Xi Yin, Xiang Yu, Kihyuk Sohn, Xiaoming Liu, Manmohan Chandraker

   Despite recent advances in face recognition using deep learning, severe accuracy drops are observed for large pose variations in unconstrained environments. Learning pose-invariant features is one solution, but needs expensively labeled large scale data and carefully designed feature learning algorithms. In this work, we focus on frontalizing faces in the ...

   Continue reading

   Keywords: Face Recognition, Face Reconstruction, 3D Shape Reconstruction, Face Synthesis, Biometrics

2019

• Gotta Adapt ’Em All: Joint Pixel and Feature-Level Domain Adaptation for Recognition in the Wild
  Luan Tran, Kihyuk Sohn, Xiang Yu, Xiaoming Liu, Manmohan Chandraker
  In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, Jun. 2019
  Bibtex | PDF | arXiv | Supplemental | Poster | Project Webpage
@inproceedings{ gotta-adapt-em-all-joint-pixel-and-feature-level-domain-adaptation-for-recognition-in-the-wild,
  author = { Luan Tran and Kihyuk Sohn and Xiang Yu and Xiaoming Liu and Manmohan Chandraker },
  title = { Gotta Adapt ’Em All: Joint Pixel and Feature-Level Domain Adaptation for Recognition in the Wild },
  booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
  address = { Long Beach, CA },
  month = { June },
  year = { 2019 },
}
• Feature Transfer Learning for Face Recognition with Under-Represented Data
  Xi Yin, Xiang Yu, Kihyuk Sohn, Xiaoming Liu, Manmohan Chandraker
  In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, Jun. 2019
  Bibtex | PDF | arXiv | Supplemental | Poster | Project Webpage
@inproceedings{ feature-transfer-learning-for-face-recognition-with-under-represented-data,
  author = { Xi Yin and Xiang Yu and Kihyuk Sohn and Xiaoming Liu and Manmohan Chandraker },
  title = { Feature Transfer Learning for Face Recognition with Under-Represented Data },
  booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
  address = { Long Beach, CA },
  month = { June },
  year = { 2019 },
}

2017

• Towards Large-Pose Face Frontalization in the Wild
  Xi Yin, Xiang Yu, Kihyuk Sohn, Xiaoming Liu, Manmohan Chandraker
  In Proceeding of International Conference on Computer Vision (ICCV 2017), Venice, Italy, Oct. 2017
  Bibtex | PDF | arXiv | Supplemental | Poster | Project Webpage
@inproceedings{ towards-large-pose-face-frontalization-in-the-wild,
  author = { Xi Yin and Xiang Yu and Kihyuk Sohn and Xiaoming Liu and Manmohan Chandraker },
  title = { Towards Large-Pose Face Frontalization in the Wild },
  booktitle = { In Proceeding of International Conference on Computer Vision },
  address = { Venice, Italy },
  month = { October },
  year = { 2017 },
}