Figure 1: Ground truth grasps and generated grasps. Each row corresponds to one object. Left three columns show the ground truth grasps, each from three different viewpoints. The middle three columns show one generated example, and the right three columns show another generated example. Note that these objects are never seen during training. See Appendix E (Fig. E.4) for more examples.

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adrian.spurr,zicong.fan,otmar.hilliges,siyu.tang}@inf.ethz.ch https://korrawe.github.io/halo Figure 1. We introduce a novel neural implicit surface representation of human hands (HALO) that is fully driven by keypoint-based skeleton articulation. Taking 3D keypoints as input, a fully differentiable implicit occupancy representation produces high-fidelity reconstruction of the hand surface (top row). We show that HALO facilitates the conditional generation of articulated hands that grasp 3D objects in a realistic and physically plausible manner (bottom row).

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