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We present a novel solution to the garment animation problem through deeplearning. Our contribution allows animating any template outfit with arbitrarytopology and geometric complexity. Recent works develop models for garmentedition, resizing and animation at the same time by leveraging the support bodymodel (encoding garments as body homotopies). This leads to complex engineeringsolutions that suffer from scalability, applicability and compatibility. Bylimiting our scope to garment animation only, we are able to propose a simplemodel that can animate any outfit, independently of its topology, vertex orderor connectivity. Our proposed architecture maps outfits to animated 3D modelsinto the standard format for 3D animation (blend weights and blend shapesmatrices), automatically providing of compatibility with any graphics engine.We also propose a methodology to complement supervised learning with anunsupervised physically based learning that implicitly solves collisions andenhances cloth quality.

DeePSD: Automatic Deep Skinning And Pose Space Deformation For 3D Garment Animation