Big news for enterprise DJI drone users as Terra, the company’s 3D modeling software, is set to get some new next-generation ...

CDimension has developed a process for growing molybdenum disulfide (MoS2), a 2D semiconductor, on silicon at a low-enough temperature that it will not damage underlying silicon circuits. That could ...

Researchers show how blister shapes in atomically thin materials like graphene can be used to map pressure, membrane tension, ...

By leveraging the concept of chirality, or the difference of a shape from its mirror image, EPFL scientists have engineered ...

2D image-based 3D shape retrieval (2D-to-3D) aims at searching the corresponding 3D shapes (unlabeled) when given a 2D image (labeled), which is a fundamental task in computer vision and has gained a ...

Keywords: 2D segmentation, 3D segmentation, LiDAR, 3D measurement, anatomical location, curvature, deep learning—artificial intelligence Citation: Chang CW, Wang H, Lai F, Christian M, Chen Huang S ...

JAVA class. Contribute to zayzigzagzz/CSC-151 development by creating an account on GitHub.

An AI method enables the generation of sharp, high-quality 3D shapes that are closer to the quality of the best 2D image models. Previous approaches typically generated blurry or cartoonish 3D shapes.

While 2D generative AI models can produce lifelike images, they aren’t designed for 3D. When applied to 3D shapes, these models most likely produce blurry or cartoonish outputs.

This journal, titled "The Geometry of Flat and Full: Comparing 2D and 3D Shapes," explores the fundamental differences and relationships between two-dimensional (2D) and three-dimensional (3D) shapes.