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Direct mesh fitting for 3D hand shape reconstruction is highly accurate.However, the reconstructed meshes are prone to artifacts and do not appear asplausible hand shapes. Conversely, parametric models like MANO ensure plausiblehand shapes but are not as accurate as the non-parametric methods. In thiswork, we introduce a novel weakly-supervised hand shape estimation frameworkthat integrates non-parametric mesh fitting with MANO model in an end-to-endfashion. Our joint model overcomes the tradeoff in accuracy and plausibility toyield well-aligned and high-quality 3D meshes, especially in challengingtwo-hand and hand-object interaction scenarios.

Overcoming the Trade-off Between Accuracy and Plausibility in 3D Hand Shape Reconstruction