核心概念
Proposing W-HMR for accurate human mesh recovery in world space by decoupling global body recovery into camera calibration, local body recovery, and global body orientation correction.
要約
The article introduces W-HMR as a solution for accurate 3D human mesh recovery in complex scenarios. It addresses the limitations of existing methods by focusing on weak-supervised camera calibration and orientation correction. The proposed method achieves high-quality reconstruction in dual coordinate systems, expanding application possibilities.
Introduction: Discusses challenges in reconstructing 3D human bodies from monocular images.
Camera Calibration: Introduces weak-supervised camera calibration to predict reasonable focal lengths.
Orientation Correction: Proposes an orientation correction module to ensure reasonable poses in world space.
Training Paradigm: Describes the three-stage training process for model development.
Other Losses: Explains additional loss functions used for refining model performance.
Implementation Details: Outlines the implementation specifics including backbone selection and dataset usage.
About Datasets: Provides information on datasets used for evaluation including AGORA, HuMMan, and SPEC-MTP.
Metrics: Details the evaluation metrics used to assess model performance.
Evaluation Results: Summarizes results on distorted datasets (AGORA, HuMMan, SPEC-MTP) and traditional benchmarks (3DPW, H36M, MPI-INF-3D).
統計
W-HMRは、人間のメッシュを正確に回復するために、カメラのキャリブレーションと方向修正を弱補助しています。
引用
"W-HMR achieves high-quality reconstruction in dual coordinate systems."
"Our contribution can be grouped into weak-supervised camera calibration and orientation correction."