QtMeshEditor Mesh Segmentation Vehicle is a point-cloud part-segmentation model designed to label points within 3D vehicle meshes. Implemented in the style of PointNet++, the model assigns each point in a mesh representing vehicles—such as cars, trucks, planes, or helicopters—to one of several categories: vehicle body, wheel, window, wing, or rotor (propeller). The model is exported in the ONNX format, enabling local inference through ONNX Runtime. This segmentation model is one of several category-specialized models built for use with QtMeshEditor, a free and open-source 3D mesh and animation editor. Within the QtMeshEditor application, a companion point-cloud classifier first detects the mesh category and then dispatches the relevant segmentation model, with this particular model handling vehicle meshes. Related models exist for other categories such as body, vegetation, and building. The model accepts a sampled point cloud as input, specifically in float32 format. QtMeshEditor Mesh Segmentation Vehicle is distributed under the Creative Commons Attribution 4.0 International (cc-by-4.0) license. The aggregate download source for this and related models is referenced as QtMeshEditor-models. The tool is intended for scenarios requiring detailed labeling of 3D vehicle mesh parts, supporting workflows in 3D mesh editing and animation.
QtMeshEditor Mesh Segmentation Vehicle is an Other AI product. It focuses on segmenting and labeling parts of 3D vehicle meshes for graphics and robotics applications. It is built as an open-source project for 3D graphics developers. QtMeshEditor Mesh Segmentation Vehicle is open source under the MIT license. The product ships for the web and the command line, and it can be self-hosted.
fernandotonon builds and maintains QtMeshEditor Mesh Segmentation Vehicle, and the product first shipped in 2020. Development happens publicly on GitHub with 40 stars and 821 commits in the last 90 days. PulseGate's similarity index finds few close equivalents — QtMeshEditor Mesh Segmentation Vehicle occupies a relatively distinct niche. Key capabilities include 3D mesh segmentation, vehicle part labeling, and open-source.
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