3D Face Modeling | 3D Human Reconstruction | 3D Object Detection | 3D Shape Correspondence | 3D Shape Generation | 3D Shape Reconstruction | Activity Recognition | Application | Biometrics | Body Matching | 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 | Person Re-identification | Plant Vision | Semantic Segmentation | Surveillance | Tracking | Typing Behavior | Vision-language

3D Shape Generation

2024

  • TIGER: Time-Varying Denoising Model for 3D Point Cloud Generation with Diffusion Process
    Zhiyuan Ren, Minchul Kim, Feng Liu, Xiaoming Liu
    In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2024), Seattle, WA, Jun. 2024
    Bibtex | PDF | Supplemental | Code
    • @inproceedings{ tiger-time-varying-denoising-model-for-3d-point-cloud-generation-with-diffusion-process,
      author = { Zhiyuan Ren and Minchul Kim and Feng Liu and Xiaoming Liu },
      title = { TIGER: Time-Varying Denoising Model for 3D Point Cloud Generation with Diffusion Process },
      booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
      address = { Seattle, WA },
      month = { June },
      year = { 2024 },
    }