Pose estimation

Precise determination of an object's position, orientation, and dimensions in 3D space is vital for autonomous driving.

Selected publications

  1. ManiPose: Manifold-Constrained Multi-Hypothesis 3D Human Pose Estimation
    Cédric Rommel, Victor Letzelter, Nermin Samet, Renaud Marlet, Matthieu Cord, Patrick Pérez, Eduardo Valle
    NeurIPS, 2024
    pdf Code
  2. Lost and Found: Overcoming Detector Failures in Online Multi-Object Tracking
    Lorenzo Vaquero, Yihong Xu, Xavier Alameda-Pineda, Víctor M. Brea, Manuel Mucientes
    ECCV, 2024
    pdf Code
  3. PAFUSE: Part-based Diffusion for 3D Whole-Body Pose Estimation
    Nermin Samet, Cédric Rommel, David Picard, Eduardo Valle
    ECCV Workshop, 2024
    pdf Code
  4. NOPE: Novel Object Pose Estimation from a Single Image
    Van Nguyen Nguyen, Thibault Groueix, Georgy Ponimatkin, Yinlin Hu, Renaud Marlet, Mathieu Salzmann, Vincent Lepetit
    CVPR, 2024
    Project page pdf Code
  5. DiffHPE: Robust, Coherent 3D Human Pose Lifting with Diffusion
    Cédric Rommel, Eduardo Valle, Mickaël Chen, Souhaiel Khalfaoui, Renaud Marlet, Matthieu Cord, Patrick Pérez
    ICCV, 2023
    pdf Code
  6. HULC: 3D HUman Motion Capture with Pose Manifold Sampling and Dense Contact Guidance
    Soshi Shimada, Vladislav Golyanik, Zhi Li, Patrick Pérez, Weipeng Xu, Christian Theobalt
    ECCV, 2022
    Project page pdf