3D Face Modeling | 3D Object Detection | 3D Shape Correspondence | 3D Shape Reconstruction | Activity Recognition | Adversarial Attacks | Anti-Spoofing | Application | Attention Mechanism | Biometrics | Data Imputation | Database | Deep Learning | Deepfake | Depth Completion | Depth Prediction | Domain Adaptation | Expression Recognition | Face Alignment | Face Antispoofing | Face Deidentification | Face Modeling | Face Recognition | Face Reconstruction | Face Relighting | Fake Faces | Forecasting | Forensics | Gait Recognition | Generic Object 3D Reconstruction | Image Alignment | Image Forgery | Image Segmentation | Joint Alignment | Learning | Low-level Vision | Medical Imaging | Motion Compensation | Multi-modality | Multimedia Retrieval | Noise Synthesis | Object Detection | Pedestrian Detection | Plant Vision | Semantic Segmentation | Sensor Fusion | Sequence Alignment | Surveillance | Tracking | Typing Behavior | Video

Generic Object 3D Reconstruction

  1. summary image

    Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image

    Feng Liu, Xiaoming Liu

    Inferring 3D locations and shapes of multiple objects from a single 2D image is a long-standing objective of computer vision. Most of the existing works either predict one of these 3D properties or focus on solving both for a single object. One fundamental challenge lies in how to learn an ...

    Continue reading

    Keywords: 3D Object Detection, 3D Shape Reconstruction, Generic Object 3D Reconstruction

2021

  • Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image
    Feng Liu, Xiaoming Liu
    In Proceeding of Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), Virtual, Dec. 2021
    Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code | Video
    • @inproceedings{ voxel-based-3d-detection-and-reconstruction-of-multiple-objects-from-a-single-image,
      author = { Feng Liu and Xiaoming Liu },
      title = { Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image },
      booktitle = { In Proceeding of Thirty-fifth Conference on Neural Information Processing Systems },
      address = { Virtual },
      month = { December },
      year = { 2021 },
    }
  • Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction
    Feng Liu, Luan Tran, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2021), Nashville, TN, Jun. 2021
    Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code | Video
    • @inproceedings{ fully-understanding-generic-objects-modeling-segmentation-and-reconstruction,
      author = { Feng Liu and Luan Tran and Xiaoming Liu },
      title = { Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Nashville, TN },
      month = { June },
      year = { 2021 },
    }