PointInfinity: Resolution-Invariant Point Diffusion Models
PointInfinity: Resolution-Invariant Point Diffusion Models
We present PointInfinity, an efficient family of point cloud diffusion models. Our core idea is to use a transformer-based architecture with a fixed-size, resolution-invariant latent representation. This enables efficient training with low-resolution point clouds, while allowing high-resolution point clouds to be generated during inference. More importantly, we show that scaling …