论文标题
基于紫外线的3D手对象重建具有GRASP优化
UV-Based 3D Hand-Object Reconstruction with Grasp Optimization
论文作者
论文摘要
我们提出了一个新的框架，用于从单个RGB图像中进行3D手形状重建和手动抓握优化。手动对象接触区域的表示对于准确的重建至关重要。我们没有像以前的作品那样近似稀疏点的接触区域，而是以紫外线坐标图的形式提出了一个密集的表示。此外，我们引入推理时间优化，以微调掌握并改善手与物体之间的相互作用。我们的管道提高了手形重建精度，并产生充满活力的手纹理。在HO3D，Freihand和DexyCB等数据集上的实验表明，我们所提出的方法的表现优于最先进的方法。
We propose a novel framework for 3D hand shape reconstruction and hand-object grasp optimization from a single RGB image. The representation of hand-object contact regions is critical for accurate reconstructions. Instead of approximating the contact regions with sparse points, as in previous works, we propose a dense representation in the form of a UV coordinate map. Furthermore, we introduce inference-time optimization to fine-tune the grasp and improve interactions between the hand and the object. Our pipeline increases hand shape reconstruction accuracy and produces a vibrant hand texture. Experiments on datasets such as Ho3D, FreiHAND, and DexYCB reveal that our proposed method outperforms the state-of-the-art.
