从单张照片重建人体与物体的3D交互，精确模拟手指抓握动作。
GraspHOI: Full-Body 3D Human-Object Reconstruction with Finger-Level Grasps from a Single In-the-Wild Image
- 分离重建人体、手部和物体，通过深度与图像空间对齐
- 显式优化手指与物体表面接触，避免穿透或悬空
- 无需预设模型或类别词典，适用于任意物体
现有单目全身3D人-物交互（HOI）方法未将精细手指抓握优化与类别无关的物体重建结合。尽管人体-物体配置合理，其手指仍可能脱离或穿入物体。我们提出GraspHOI，首个从单张图像中重建全身3D HOI并显式优化手指关节以贴合重构物体的框架。该方法直接恢复物体几何形状，无需预定义网格或固定类别词典。身体、双手和物体分别重建，并通过基于深度的配准与图像空间对齐，在度量相机空间中统一。遮挡感知的掌面对应关系将物体定位在抓握手掌上，接触感知优化调整手臂与手指关节，确保表面接触且无过度穿透。在四个基准和六种基线中，GraspHOI提升了相对人-物位置、手部精度和接触合理性。完整代码将公开。
原文摘要 · Abstract (English)
Existing monocular full-body 3D human-object interaction (HOI) methods do not combine explicit finger-level grasp optimization with category-agnostic object reconstruction. Despite plausible body-object configurations, their fingers may float from or penetrate objects instead of forming a grasp. We present GraspHOI, the first framework that reconstructs a full-body 3D HOI from a single image while explicitly optimizing finger articulation against the reconstructed object. GraspHOI recovers object geometry directly, without predefined meshes or a fixed category vocabulary. It reconstructs the body, hands, and object separately, aligning them in metric camera space via depth-based registration and image-space alignment. Occlusion-aware palmar correspondences seat the object against the grasping hand, and contact-aware optimization refines arm and finger articulation to form surface contact without excessive penetration. Across four benchmarks and six baselines, GraspHOI improves relative human-object placement, hand accuracy, and contact plausibility. Full pipeline code will be released.
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