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AI 3D model generators are software tools that use artificial intelligence to create virtual three-dimensional objects. These objects can be used in a variety of applications, ranging from animation to architecture and engineering. AI 3D model generators typically offer more realistic results than traditional methods, due to their ability to simulate physical characteristics such as textures and lighting. They are also capable of creating models with greater detail than manual methods, allowing for high-quality visuals in a shorter time frame.
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Point cloud processing software is designed to manipulate, analyze, and visualize 3D data captured by various scanning technologies such as LiDAR or photogrammetry. It enables users to process large sets of spatial data points into accurate 3D models, which can be used in fields like architecture, engineering, construction, and environmental monitoring. Key features often include noise reduction, data segmentation, feature extraction, and mesh generation to create usable surfaces from raw point clouds. The software may also provide tools for registering multiple point clouds together into a unified coordinate system or for aligning them with existing CAD models. Ultimately, point cloud processing software helps convert raw spatial data into actionable insights, aiding in design, planning, and decision-making processes.
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    Point-E

    Point-E

    OpenAI

    While recent work on text-conditional 3D object generation has shown promising results, the state-of-the-art methods typically require multiple GPU-hours to produce a single sample. This is in stark contrast to state-of-the-art generative image models, which produce samples in a number of seconds or minutes. In this paper, we explore an alternative method for 3D object generation which produces 3D models in only 1-2 minutes on a single GPU. Our method first generates a single synthetic view...
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