Point cloud completion is crucial for 3D computer vision tasks in autonomous driving, augmented reality, and robotics. However, obtaining clean and complete point clouds from real-world environments ...

Abstract: This article proposes a multimodal human pose reconstruction method based on 3-D ultrawideband (UWB) radar images and point clouds, aiming to improve the accuracy of human pose estimation ...

3D scanning is becoming much more accessible, which means it’s more likely that the average hacker will use it to solve problems — possibly odd ones. That being the case, a handy tool to have in one’s ...

This episode looks at the "point clouds" for 3D data visuals used in architecture, archaeology, and autonomous driving. Plus, robots learn new moves. Point cloud data is captured with LiDAR. Captured ...

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 ...