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

Depth Prediction

  1. summary image

    Depth Completion with TWIN Surface Extrapolation at Occlusion Boundaries

    Saif Imran, Xiaoming Liu, Daniel Morris

    Depth completion starts from a sparse set of known depth values and estimates the unknown depths for the remaining image pixels. Most methods model this as depth interpolation and erroneously interpolate depth pixels into the empty space between spatially distinct objects, resulting in depth-smearing across occlusion boundaries. Here we propose ...

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    Keywords: Depth Completion, Camera+LiDAR+Radar, Depth Prediction

  2. summary image

    The Edge of Depth: Explicit Constraints between Segmentation and Depth

    Shengjie Zhu, Garrick Brazil, Xiaoming Liu

    In this work we study the mutual benefits of two common computer vision tasks, self-supervised depth estimation and semantic segmentation from images. For example, to help unsupervised monocular depth estimation, constraints from semantic segmentation has been explored implicitly such as sharing and transforming features. In contrast, we propose to explicitly ...

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    Keywords: Depth Prediction, Image Segmentation, Semantic Segmentation

  3. summary image

    Depth Coefficients for Depth Completion

    Saif Imran, Yunfei Long, Xiaoming Liu, Daniel Morris

    Depth completion involves estimating a dense depth image from sparse depth measurements, often guided by a color image. While linear upsampling is straight forward, it results in artifacts including depth pixels being interpolated in empty space across discontinuities between objects. Current methods use deep networks to upsample and "complete" the ...

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    Keywords: Depth Completion, Camera+LiDAR+Radar, Multi-modality, Depth Prediction

2021

  • Depth Completion with Twin-Surface Extrapolation at Occlusion Boundaries
    Saif Imran, Xiaoming Liu, Daniel Morris
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2021), Nashville, TN, Jun. 2021
    Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code | Video
  • @inproceedings{ depth-completion-with-twin-surface-extrapolation-at-occlusion-boundaries,
      author = { Saif Imran and Xiaoming Liu and Daniel Morris },
      title = { Depth Completion with Twin-Surface Extrapolation at Occlusion Boundaries },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Nashville, TN },
      month = { June },
      year = { 2021 },
    }
  • Radar-Camera Pixel Depth Association for Depth Completion
    Yunfei Long, Daniel Morris, Xiaoming Liu, Marcos Paul Gerardo Castro, Punarjay Chakravarty, Praveen Narayanan
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2021), Nashville, TN, Jun. 2021
    Bibtex | arXiv | Code | Video
  • @inproceedings{ radar-camera-pixel-depth-association-for-depth-completion,
      author = { Yunfei Long and Daniel Morris and Xiaoming Liu and Marcos Paul Gerardo Castro and Punarjay Chakravarty and Praveen Narayanan },
      title = { Radar-Camera Pixel Depth Association for Depth Completion },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Nashville, TN },
      month = { June },
      year = { 2021 },
    }

2020

  • The Edge of Depth: Explicit Constraints between Segmentation and Depth
    Shengjie Zhu, Garrick Brazil, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, Jun. 2020
    Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code | Video
  • @inproceedings{ the-edge-of-depth-explicit-constraints-between-segmentation-and-depth,
      author = { Shengjie Zhu and Garrick Brazil and Xiaoming Liu },
      title = { The Edge of Depth: Explicit Constraints between Segmentation and Depth },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Seattle, WA },
      month = { June },
      year = { 2020 },
    }

2019

  • Depth Coefficients for Depth Completion
    Saif Imran, Yunfei Long, Xiaoming Liu, Daniel Morris
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, Jun. 2019
    Bibtex | PDF | arXiv | Supplemental | Poster | Project Webpage | Code | Video
  • @inproceedings{ depth-coefficients-for-depth-completion,
      author = { Saif Imran and Yunfei Long and Xiaoming Liu and Daniel Morris },
      title = { Depth Coefficients for Depth Completion },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Long Beach, CA },
      month = { June },
      year = { 2019 },
    }

2017

  • Face Anti-Spoofing Using Patch and Depth-based CNNs
    Yousef Atoum, Yaojie Liu, Amin Jourabloo, Xiaoming Liu
    In Proceeding of International Joint Conference on Biometrics (IJCB 2017), Denver, CO, Oct. 2017
    Bibtex | PDF | Poster | Project Webpage
  • @inproceedings{ face-anti-spoofing-using-patch-and-depth-based-cnns,
      author = { Yousef Atoum and Yaojie Liu and Amin Jourabloo and Xiaoming Liu },
      title = { Face Anti-Spoofing Using Patch and Depth-based CNNs },
      booktitle = { In Proceeding of International Joint Conference on Biometrics },
      address = { Denver, CO },
      month = { October },
      year = { 2017 },
    }