3D Face Modeling | 3D Object Detection | 3D Shape Correspondence | 3D Shape Reconstruction | Activity Recognition | Application | Biometrics | Camera Calibration | Camera+LiDAR+Radar | Data Imputation | Database | Depth Completion | Depth Prediction | Domain Adaptation | Expression Recognition | Face Alignment | Face Antispoofing | Face Deidentification | Face Recognition | Face Reconstruction | Face Relighting | Face Synthesis | Forecasting | Gait Recognition | Generic Object 3D Reconstruction | Image Alignment | Image Manipulation | Image Segmentation | Low-level Vision | Medical Imaging | Motion Compensation | Multi-modality | Multimedia Retrieval | Object Detection | Pedestrian Detection | Plant Vision | Semantic Segmentation | Surveillance | Tracking | Typing Behavior

Database

  1. summary image

    Face Anti-spoofing, Face Presentation Attack Detection

    Yaojie Liu, Joel Stehouwer, Amin Jourabloo, Yousef Atoum, Xiaoming Liu

    Biometrics utilize physiological, such as fingerprint, face, and iris, or behavioral characteristics, such as typing rhythm and gait, to uniquely identify or authenticate an individual. As biometric systems are widely used in real-world applications including mobile phone authentication and access control, biometric spoof, or Presentation Attack (PA) are becoming a ...

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    Keywords: Face Antispoofing, Biometrics, Low-level Vision, Database

  2. summary image

    Facial Forgery Detection

    Hao Dang*, Feng Liu*, Joel Stehouwer*, Xiaoming Liu, Anil Jain

    The prevalence of facial recognition, biometric unlock, and social media presents a significant opportunity for bad actors to introduce forged or manipulated images to spread false information or damage reputations. This is aided by the continuing improvement in realistic image synthesis and manipulation by generative adversarial network, GAN, based methods ...

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    Keywords: Image Manipulation, Low-level Vision, Database

  3. summary image

    Generic Object Sensor and Spoof Noise Classification, Modeling, and Synthesis

    Joel Stehouwer, Amin Jourabloo, Yaojie Liu, Xiaoming Liu

    Biometric recognition is increasingly used in commercial and high-security settings. Because of this, the threat of spoofing techniques, the act of presenting a fake biometric object to a sensor, is a large concern. Recent research has focused on face, fingerprint, and iris anti-spoofing. However, no other research attempts to use ...

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    Keywords: Low-level Vision, Database

  4. 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: Biometrics, Gait Recognition, Database

  5. summary image

    Sports Videos in the Wild (SVW): A Video Dataset for Sports Analysis

    Seyed Morteza Safdarnejad, Xiaoming Liu, Lalita Udpa, Brooks Andrus, John Wood, Dean Craven

    The amount of digital videos being created is increasing exponentially, e.g., YouTube has reached the upload rate of 100 hours of video per minute. A great deal of this growth is due to the tremendous popularity of smartphones and ubiquitous Internet access. This means that amateur-user generated videos form ...

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    Keywords: Activity Recognition, Database, Application

  6. summary image

    Multi-Modality Imagery Database for Plant Phenotyping

    Jeffrey A. Cruz, Xi Yin, Xiaoming Liu, Saif M. Imran, Daniel D. Morris, David M. Kramer, Jin Chen

    We have collected a multi-modality plant imagery database named “MSU-PID” including two types of plants: Arabidopsis and bean. It is captured using four types of imaging sensors:fluorescence, infrared(IR), RGB color, and depth. The imaging setup and the variety of manual labels allow MSU-PID to be used for a ...

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    Keywords: Plant Vision, Database, Application, Multi-Modality

2022

  • Multi-domain Learning for Updating Face Anti-spoofing Models
    Xiao Guo, Yaojie Liu, Anil Jain, Xiaoming Liu
    In Proceeding of European Conference on Computer Vision (ECCV 2022), Tel-Aviv, Israel, Oct. 2022 (Oral presentation)
    Bibtex | PDF | arXiv | Supplemental | Code
  • @inproceedings{ multi-domain-learning-for-updating-face-anti-spoofing-models,
      author = { Xiao Guo and Yaojie Liu and Anil Jain and Xiaoming Liu },
      title = { Multi-domain Learning for Updating Face Anti-spoofing Models },
      booktitle = { In Proceeding of European Conference on Computer Vision },
      address = { Tel-Aviv, Israel },
      month = { October },
      year = { 2022 },
    }
  • Blind Removal of Facial Foreign Shadows
    Yaojie Liu*, Andrew Hou*, Xinyu Huang, Liu Ren, Xiaoming Liu
    In Proceedings of British Machine Vision Conference (BMVC), London, UK, Nov. 2022
    Bibtex | PDF | Supplemental
  • @inproceedings{ blind-removal-of-facial-foreign-shadows,
      author = { Yaojie Liu* and Andrew Hou* and Xinyu Huang and Liu Ren and Xiaoming Liu },
      title = { Blind Removal of Facial Foreign Shadows },
      booktitle = { In Proceedings of British Machine Vision Conference (BMVC) },
      address = { London, UK },
      month = { November },
      year = { 2022 },
    }

2021

  • Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images
    Vishal Asnani, Xi Yin, Tal Hassner, Xiaoming Liu
    IEEE Transactions on Pattern Analysis and Machine Intelligence, , Apr. 2021 (Under Review)
    Bibtex | PDF | arXiv | Code | Dataset
  • @article{ reverse-engineering-of-generative-models-inferring-model-hyperparameters-from-generated-images,
      author = { Vishal Asnani and Xi Yin and Tal Hassner and Xiaoming Liu },
      title = { Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images },
      journal = { IEEE Transactions on Pattern Analysis and Machine Intelligence },
      month = { April },
      year = { 2021 },
    }

2020

  • On Learning Disentangled Representations for Gait Recognition
    Ziyuan Zhang, Luan Tran, Feng Liu, Xiaoming Liu
    IEEE Transactions on Pattern Analysis and Machine Intelligence, , May. 2020 (in press)
    Bibtex | PDF | arXiv | Project Webpage | Code
  • @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 = { May },
      year = { 2020 },
    }
  • On the Detection of Digital Face Manipulation
    Hao Dang*, Feng Liu*, Joel Stehouwer*, Xiaoming Liu, Anil Jain
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, Jun. 2020
    Bibtex | PDF | arXiv | Supplemental | Poster | Project Webpage | Code
  • @inproceedings{ on-the-detection-of-digital-face-manipulation,
      author = { Hao Dang* and Feng Liu* and Joel Stehouwer* and Xiaoming Liu and Anil Jain },
      title = { On the Detection of Digital Face Manipulation },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Seattle, WA },
      month = { June },
      year = { 2020 },
    }
  • Noise Modeling, Synthesis and Classification for Generic Object Anti-Spoofing
    Joel Stehouwer, Amin Jourabloo, Yaojie Liu, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, Jun. 2020
    Bibtex | PDF | arXiv | Poster | Project Webpage | Code
  • @inproceedings{ noise-modeling-synthesis-and-classification-for-generic-object-anti-spoofing,
      author = { Joel Stehouwer and Amin Jourabloo and Yaojie Liu and Xiaoming Liu },
      title = { Noise Modeling, Synthesis and Classification for Generic Object Anti-Spoofing },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Seattle, WA },
      month = { June },
      year = { 2020 },
    }

2019

  • Deep Tree Learning for Zero-shot Face Anti-Spoofing
    Yaojie Liu, Joel Stehouwer, Amin Jourabloo, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, Jun. 2019 (Oral Presentation, Best Paper Award Finalist)
    Bibtex | PDF | arXiv | Poster | Project Webpage | Code | Video
  • @inproceedings{ deep-tree-learning-for-zero-shot-face-anti-spoofing,
      author = { Yaojie Liu and Joel Stehouwer and Amin Jourabloo and Xiaoming Liu },
      title = { Deep Tree Learning for Zero-shot Face Anti-Spoofing },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Long Beach, CA },
      month = { June },
      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 | Code
  • @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 },
    }

2018

  • Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision
    Yaojie Liu*, Amin Jourabloo*, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2018), Salt Lake City, UT, Jun. 2018
    Bibtex | PDF | arXiv | Poster | Project Webpage | Code
  • @inproceedings{ learning-deep-models-for-face-anti-spoofing-binary-or-auxiliary-supervision,
      author = { Yaojie Liu* and Amin Jourabloo* and Xiaoming Liu },
      title = { Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Salt Lake City, UT },
      month = { June },
      year = { 2018 },
    }

2016

  • Multi-modality Imagery Database for Plant Phenotyping
    Jeffrey Cruz, Xi Yin, Xiaoming Liu, Saif Imran, Daniel Morris, David Kramer, Jin Chen
    Machine Vision and Applications, Vol. 27, No. 5, pp.735-749, , Jul. 2016 (equal contribution by first two authors)
    Bibtex | PDF | Project Webpage
  • @article{ multi-modality-imagery-database-for-plant-phenotyping,
      author = { Jeffrey Cruz and Xi Yin and Xiaoming Liu and Saif Imran and Daniel Morris and David Kramer and Jin Chen },
      title = { Multi-modality Imagery Database for Plant Phenotyping },
      journal = { Machine Vision and Applications },
      volume = { 27 },
      number = { 5 },
      month = { July },
      year = { 2016 },
      pages = { 735--749 },
    }

2015

  • Sports Videos in the Wild (SVW): A Video Dataset for Sports Analysis
    Seyed Morteza Safdarnejad, Xiaoming Liu, Lalita Udpa, Brooks Andrus, John Wood, Dean Craven
    Proc. International Conference on Automatic Face and Gesture Recognition (FG 2015), Ljubljana, Slovenia, May. 2015 (Acceptance rate 84/221 = 38%)
    Bibtex | PDF | Project Webpage
  • @inproceedings{ sports-videos-in-the-wild-svw-a-video-dataset-for-sports-analysis,
      author = { Seyed Morteza Safdarnejad and Xiaoming Liu and Lalita Udpa and Brooks Andrus and John Wood and Dean Craven },
      title = { Sports Videos in the Wild (SVW): A Video Dataset for Sports Analysis },
      booktitle = { Proc. International Conference on Automatic Face and Gesture Recognition },
      address = { Ljubljana, Slovenia },
      month = { May },
      year = { 2015 },
    }

2005

  • The CMU Face In Action (FIA) Database
    Rodney Goh, Lihao Liu, Xiaoming Liu, Tsuhan Chen
    Proc. IEEE International Workshop on Analysis and Modeling of Faces and Gestures, held in conjunction with ICCV, Beijing, China, Oct. 2005
    Bibtex | PDF
  • @inproceedings{ the-cmu-face-in-action-fia-database,
      author = { Rodney Goh and Lihao Liu and Xiaoming Liu and Tsuhan Chen },
      title = { The CMU Face In Action (FIA) Database },
      booktitle = { Proc. IEEE International Workshop on Analysis and Modeling of Faces and Gestures, held in conjunction with ICCV },
      address = { Beijing, China },
      month = { October },
      year = { 2005 },
    }