Several computer vision tasks require perceiving or interacting with 3D environments and objects therein, making a strong case in favor of 3D deep learning. However, unlike images which are most ...

The automatic detection of surface-level irregularities—defects or anomalies—in 3D data is of significant interest for ...

In the coming decades, it seems inevitable that architects will increasingly focus on renovations and rehabilitations –especially in established urban centers–, whether to modernize outdated ...

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 ...

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 ...

Traditional 3D models made up of surfaces have for a long time aided us in visualizing buildings and spaces, but they often come at a cost: large models require a lot of storage and processing power, ...