ShapeFlow: Learnable Deformations Among 3D Shapes

Understand

We present ShapeFlow, a flow-based model for learning a deformation space for entire classes of 3D shapes with large intra-class variations.

• ShapeFlow allows learning a multi-template deformation space that is agnostic to shape topology, yet preserves fine geometric details.
• Different from a generative space where a latent vector is directly decoded into a shape, a deformation space decodes a vector into a continuous flow that can advect a source shape towards a target.
• Such a space naturally allows the disentanglement of geometric style (coming from the source) and structural pose (conforming to the target).