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Functional Diffusion

We propose a new class of generative diffusion models, called functional diffusion. In contrast to previous work, functional diffusion works on samples that are represented by functions with a continuous domain. Functional diffusion can be seen as an …

Motion2VecSets: 4D Latent Vector Set Diffusion for Non-rigid Shape Reconstruction and Tracking

We introduce Motion2VecSets, a 4D diffusion model for dynamic surface reconstruction from point cloud sequences. While existing state-of-the-art methods have demonstrated success in reconstructing non-rigid objects using neural field representations, …

3DILG: Irregular Latent Grids for 3D Generative Modeling

We proposed a method for representing shapes as irregular latent grids. This representation enables 3d generative modeling with autoregressive transformers.

Training Data Generating Networks: Shape Reconstruction via Bi-level Optimization

We found a link between shape reconstruction and few-shot learning.

Intuitive and Efficient Roof Modeling for Reconstruction and Synthesis

We propose a novel and flexible roof modeling approach that can be used for constructing planar 3D polygon roof meshes. Our method uses a graph structure to encode roof topology and enforces the roof validity by optimizing a simple but effective …

Point cloud instance segmentation using probabilistic embeddings

Point cloud instance segmentation