Point-E is mainly composed of two models: a model that generates images from text and a model that generates point cloud data from images. A model that generates images from text is a model that ...

In the original paper, the authors applied diffusion probabilistic models to the task of 3D point cloud generation and proposed a denoising model based on PointNet as a feature extraction network. By ...

Point-E, unlike similar systems, "leverages a large corpus of (text, image) pairs, allowing it to follow diverse and complex prompts, while our image-to-3D model is trained on a smaller dataset of ...

Abstract: Although point cloud-based 3D object detectors have advanced significantly in recent years, they are frequently hindered by substantial computational overheads. Lightweight model techniques, ...

Abstract: Point cloud completion aims to reconstruct complete 3D shapes from partial scans. The long-range dependencies between points and shape perception are crucial for this task. While ...