Im2Hands: Learning Attentive Implicit Representation of Interacting Two-Hand Shapes
Jihyun Lee, Minhyuk Sung, Honggyu Choi, Tae-Kyun Kim
Abstract
Image alignment Reconstruction Zoom-in Input Image alignment Reconstruction Zoom-in IntagHand Im2Hands (ours) Observation Reconstruction Image alignment Image alignment Reconstruction IntagHand [23] Im2Hands (Ours) Figure 1. Reconstructed two-hand shapes from an RGB image. We present Im2Hands, the first neural implicit representation for two interacting hands. Compared to the existing mesh-based two-hand reconstruction method (IntagHand [23]), Im2Hands effectively captures the fine-grained geometry of two hands with higher shape-to-image coherency. The above results were produced from a single RGB image input, where ours utilized an off-the-shelf two-hand keypoint estimation method (DIGIT [11]) to condition the articulated occupancy.
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Install the CLIlune papers fulltext 350446cc-5967-4e97-87a7-25f237349002Cited by top-tier papers12
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