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openMVS is a multi-view stereo library and photogrammetry pipeline used for 3D scene reconstruction. It transforms Structure from Motion data—specifically camera poses and sparse point clouds—into detailed 3D models consisting of dense point clouds and textured meshes.
The main features of cdcseacave/openmvs are: Neural Scene Reconstructions, 3D Reconstruction Pipelines, Dense Reconstruction Backends, Multi-View Stereo Generators, Point-to-Mesh Conversions, Point Cloud Surface Extraction, Point Cloud Generation, 3D Mesh Generators.
Projects with overlapping indexed features include: colmap/colmap — COLMAP is a 3D scene reconstruction suite and C++ geometry library that implements a full structure-from-motion… mapillary/opensfm — OpenSfM is a computer vision library and structure-from-motion pipeline designed to reconstruct three-dimensional… openmvg/openmvg — openMVG is a computer vision geometry library and toolkit for multiple view geometry. It serves as a framework for… google-research/multinerf — MultiNeRF is a 3D scene reconstruction suite and framework for training Neural Radiance Fields to synthesize novel… opendronemap/opendronemap — A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷. openmoonray/openmoonray — OpenMoonray is a production-grade physically based rendering system and path-tracing engine. It simulates the physical…
COLMAP is a 3D scene reconstruction suite and C++ geometry library that implements a full structure-from-motion pipeline. It functions as a GPU-accelerated photogrammetry tool and multi-view stereo framework designed to produce dense 3D geometry and watertight meshes from collections of 2D images. The project distinguishes itself through hardware-accelerated feature extraction and a modular camera modeling system that supports perspective, fisheye, and equirectangular lens types. It employs vocabulary tree image retrieval to efficiently identify similar images in large datasets and provides P
OpenSfM is a computer vision library and structure-from-motion pipeline designed to reconstruct three-dimensional scenes and camera trajectories from overlapping images. It functions as a 3D reconstruction engine and photogrammetry toolkit, utilizing automated feature-based image matching and incremental bundle adjustment to derive spatial geometry. The system distinguishes itself as a geospatial alignment tool, integrating GPS and inertial sensor data to align reconstructed 3D models with real-world geographic coordinates. It employs a hybrid Python and C++ execution model to manage large-sc
openMVG is a computer vision geometry library and toolkit for multiple view geometry. It serves as a framework for structure from motion and 3D scene reconstruction, providing the tools necessary to recover 3D point clouds and camera poses from collections of 2D images. The library implements both global and incremental structure-from-motion pipelines. It uses geometric algorithms to calculate camera pose estimation and image localization, employing Levenberg-Marquardt bundle adjustment to refine 3D coordinates and camera parameters by minimizing reprojection error. The project covers a broa
MultiNeRF is a 3D scene reconstruction suite and framework for training Neural Radiance Fields to synthesize novel views from sets of 2D images. It provides a system for generating new perspectives of a scene by optimizing a neural network based on images and camera poses. The toolkit includes research implementations such as Mip-NeRF 360 and Ref-NeRF for high-fidelity volumetric rendering. It features a structure-from-motion pipeline to calculate camera positions and orientations from image datasets to prepare data for training. The project covers a full workflow for volumetric rendering, i