Search Results for "sparse"

TRELLIS.2 is a cutting-edge open-source model and codebase for high-fidelity 3D asset generation from 2D images, developed to push forward the state of the art in image-to-3D generation. At its core is a novel sparse voxel structure called O-Voxel that jointly encodes both geometry and surface appearance, enabling reconstruction and generation of complex 3D shapes with arbitrary topology, open surfaces, and physically based rendering (PBR) textures. The system leverages a large 4-billion-parameter architecture combining sparse 3D variational autoencoders with flow-matching transformers to produce fully textured 3D models at resolutions up to 1536³ voxels. ...

The Objectron dataset is a collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. In each video, the camera moves around the object, capturing it from different angles. The data also contain manually annotated 3D bounding boxes for each object, which describe the object’s position, orientation, and dimensions. The dataset consists of 15K annotated video clips supplemented with over 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes. ...

cvsba is an OpenCV wrapper for the well-known Sparse Bundle Adjustment library (sba) by M. Lourakis. The main features are: - Based on sba-1.6, one of the most popular and robust bundle adjustment implementation, which is extensively used and tested by the community - sba installation is not needed since it is included in cvsba - New CMake structure which makes the library compilation, installation and linkage easier - Similar interface than Bundle Adjustment implementation on cv::LevMarqSparse::bundleAdjust() - Include examples to test the library on synthetically generated data - GPL licence