Projects

  1. summary image

    Gait Recognition via Disentangled Representation Learning

    Ziyuan Zhang, Luan Tran, Xi Yin, Yousef Atoum, Xiaoming Liu, Jian Wan, Nanxin Wang

    Gait, the walking pattern of individuals, is one of the most important biometrics modalities. Most of the existing gait recognition methods take silhouettes or articulated body models as the gait features. These methods suffer from degraded recognition performance when handling confounding variables, such as clothing, carrying and view angle. To ...

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    Keywords: Gait Recognition

  2. summary image

    Towards Interpretable Face Recognition

    Bangjie Yin, Luan Tran, Haoxiang Li, Xiaohui Shen, Xiaoming Liu

    Deep CNNs have been pushing the frontier of visual recognition over past years. Besides recognition accuracy, strong demands in understanding deep CNNs in the research community motivate developments of tools to dissect pre-trained models to visualize how they make predictions. Recent works further push the interpretability in the network learning ...

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    Keywords: Face recognition

  3. summary image

    MSU-AVIS dataset: Fusing Face and Voice Modalities for Biometric Recognition in Indoor Surveillance Videos

    Anurag Chowdhury, Yousef Atoum, Luan Tran, Xiaoming Liu, Arun Ross

    Indoor video surveillance systems often use the face modality to establish the identity of a person of interest. However, the face image may not offer sufficient discriminatory information in many scenarios due to substantial variations in pose, illumination, expression, resolution and distance between the subject and the camera.

    In such ...

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    Keywords: Application

  4. summary image

    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 ...

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    Keywords: Domain Adaptation

  5. summary image

    Disentangled Representation Learning GAN for Pose-Invariant Face Recognition

    Luan Tran, Xi Yin, Xiaoming Liu

    The large pose discrepancy between two face images is one of the fundamental challenges in automatic face recognition. Conventional approaches to pose-invariant face recognition either perform face frontalization on, or learn a pose-invariant representation from, a non-frontal face image. We argue that it is more desirable to perform both tasks ...

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    Keywords: Face Recognition, Face Reconstruction

Publications

2019

  • On Learning Disentangled Representations for Gait Recognition
    Ziyuan Zhang, Luan Tran, Feng Liu, Xiaoming Liu
    IEEE Transactions on Pattern Analysis and Machine Intelligence, , Sep. 2019 (Under Review)
    Bibtex | PDF | arXiv | Project Webpage
  • @article{ on-learning-disentangled-representations-for-gait-recognition,
      author = { Ziyuan Zhang and Luan Tran and Feng Liu and Xiaoming Liu },
      title = { On Learning Disentangled Representations for Gait Recognition },
      journal = { IEEE Transactions on Pattern Analysis and Machine Intelligence },
      month = { September },
      year = { 2019 },
    }
  • On Learning 3D Face Morphable Model from In-the-wild Images
    Luan Tran, Xiaoming Liu
    IEEE Transactions on Pattern Analysis and Machine Intelligence, , Jun. 2019 (in press)
    Bibtex | PDF | arXiv | Project Webpage
  • @article{ on-learning-3d-face-morphable-model-from-in-the-wild-images,
      author = { Luan Tran and Xiaoming Liu },
      title = { On Learning 3D Face Morphable Model from In-the-wild Images },
      journal = { IEEE Transactions on Pattern Analysis and Machine Intelligence },
      month = { June },
      year = { 2019 },
    }
  • 3D Face Modeling from Diverse Raw Scan Data
    Feng Liu, Luan Tran, Xiaoming Liu
    In Proceeding of International Conference on Computer Vision (ICCV 2019), Seoul, South Korea, Oct. 2019 (Oral presentation)
    Bibtex | PDF | arXiv | Project Webpage | Video
  • @inproceedings{ 3d-face-modeling-from-diverse-raw-scan-data,
      author = { Feng Liu and Luan Tran and Xiaoming Liu },
      title = { 3D Face Modeling from Diverse Raw Scan Data },
      booktitle = { In Proceeding of International Conference on Computer Vision },
      address = { Seoul, South Korea },
      month = { October },
      year = { 2019 },
    }
  • Towards Interpretable Face Recognition
    Bangjie Yin*, Luan Tran*, Haoxiang Li, Xiaohui Shen, Xiaoming Liu
    In Proceeding of International Conference on Computer Vision (ICCV 2019), Seoul, South Korea, Oct. 2019 (Oral presentation)
    Bibtex | PDF | arXiv | Project Webpage | Video
  • @inproceedings{ towards-interpretable-face-recognition,
      author = { Bangjie Yin* and Luan Tran* and Haoxiang Li and Xiaohui Shen and Xiaoming Liu },
      title = { Towards Interpretable Face Recognition },
      booktitle = { In Proceeding of International Conference on Computer Vision },
      address = { Seoul, South Korea },
      month = { October },
      year = { 2019 },
    }
  • Gait Recognition via Disentangled Representation Learning
    Ziyuan Zhang, Luan Tran, Xi Yin, Yousef Atoum, Jian Wan, Nanxin Wang, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, Jun. 2019 (Oral presentation)
    Bibtex | PDF | arXiv | Project Webpage
  • @inproceedings{ gait-recognition-via-disentangled-representation-learning,
      author = { Ziyuan Zhang and Luan Tran and Xi Yin and Yousef Atoum and Jian Wan and Nanxin Wang and Xiaoming Liu },
      title = { Gait Recognition via Disentangled Representation Learning },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Long Beach, CA },
      month = { June },
      year = { 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 },
    }
  • Towards High-fidelity Nonlinear 3D Face Morphable Model
    Luan Tran, Feng Liu, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, Jun. 2019
    Bibtex | PDF | arXiv | Poster | Project Webpage
  • @inproceedings{ towards-high-fidelity-nonlinear-3d-face-morphable-model,
      author = { Luan Tran and Feng Liu and Xiaoming Liu },
      title = { Towards High-fidelity Nonlinear 3D Face Morphable Model },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Long Beach, CA },
      month = { June },
      year = { 2019 },
    }

2018

  • Representation Learning by Rotating Your Faces
    Luan Tran, Xi Yin, Xiaoming Liu
    IEEE Transactions on Pattern Analysis and Machine Intelligence, , Sep. 2018 (in press)
    Bibtex | PDF | arXiv | Project Webpage
  • @article{ representation-learning-by-rotating-your-faces,
      author = { Luan Tran and Xi Yin and Xiaoming Liu },
      title = { Representation Learning by Rotating Your Faces },
      journal = { IEEE Transactions on Pattern Analysis and Machine Intelligence },
      month = { September },
      year = { 2018 },
    }
  • Nonlinear 3D Face Morphable Model
    Luan Tran, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2018), Salt Lake City, UT, Jun. 2018 (Spotlight)
    Bibtex | PDF | arXiv | Poster | Project Webpage
  • @inproceedings{ nonlinear-3d-face-morphable-model,
      author = { Luan Tran and Xiaoming Liu },
      title = { Nonlinear 3D Face Morphable Model },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Salt Lake City, UT },
      month = { June },
      year = { 2018 },
    }
  • MSU-AVIS dataset: Fusing Face and Voice Modalities for Biometric Recognition in Indoor Surveillance Videos
    Anurag Chowdhury, Yousef Atoum, Luan Tran, Xiaoming Liu, Arun Ross
    In Proceeding of International Conference on Pattern Recognition (ICPR 2018), Beijing, China, Aug. 2018
    Bibtex | PDF | Poster | Project Webpage
  • @inproceedings{ msu-avis-dataset-fusing-face-and-voice-modalities-for-biometric-recognition-in-indoor-surveillance-videos,
      author = { Anurag Chowdhury and Yousef Atoum and Luan Tran and Xiaoming Liu and Arun Ross },
      title = { MSU-AVIS dataset: Fusing Face and Voice Modalities for Biometric Recognition in Indoor Surveillance Videos },
      booktitle = { In Proceeding of International Conference on Pattern Recognition },
      address = { Beijing, China },
      month = { August },
      year = { 2018 },
    }

2017

  • Disentangled Representation Learning GAN for Pose-Invariant Face Recognition
    Luan Tran, Xi Yin, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2017), Honolulu, HI, Jul. 2017 (Oral presentation)
    Bibtex | PDF | Project Webpage
  • @inproceedings{ disentangled-representation-learning-gan-for-pose-invariant-face-recognition,
      author = { Luan Tran and Xi Yin and Xiaoming Liu },
      title = { Disentangled Representation Learning GAN for Pose-Invariant Face Recognition },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Honolulu, HI },
      month = { July },
      year = { 2017 },
    }
  • Missing Modalities Imputation via Cascaded Residual Autoencoder
    Luan Tran, Xiaoming Liu, Jiayu Zhou, Rong Jin
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2017), Honolulu, HI, Jul. 2017
    Bibtex | PDF | Project Webpage
  • @inproceedings{ missing-modalities-imputation-via-cascaded-residual-autoencoder,
      author = { Luan Tran and Xiaoming Liu and Jiayu Zhou and Rong Jin },
      title = { Missing Modalities Imputation via Cascaded Residual Autoencoder },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Honolulu, HI },
      month = { July },
      year = { 2017 },
    }