PolyGen: An Autoregressive Generative Model of 3D Meshes

Understand

Polygon meshes are an efficient representation of 3D geometry, and are of central importance in computer graphics, robotics and games development.

• Existing learning-based approaches have avoided the challenges of working with 3D meshes, instead using alternative object representations that are more compatible with neural architectures and training approaches.
• We present an approach which models the mesh directly, predicting mesh vertices and faces sequentially using a Transformer-based architecture.
• Our model can condition on a range of inputs, including object classes, voxels, and images, and because the model is probabilistic it can produce samples that capture uncertainty in ambiguous scenarios.