3 articles tagged with #mesh-generation. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Researchers introduce Dmsh, a fully automated reinforcement learning framework that generates high-quality all-quadrilateral meshes for arbitrary geometries using three coordinated agents. The system formulates mesh generation as a Markov Decision Process and demonstrates superior performance compared to existing methods across multiple benchmarks.
City-Mesh3R introduces a scalable framework for reconstructing high-fidelity 3D city-scale meshes directly from unordered image collections using a divide-and-conquer strategy. The method addresses limitations of existing NeRF and Gaussian Splatting approaches by producing watertight, simulation-ready meshes suitable for large urban scenes without prohibitive computational overhead.
AssetGen is a new 3D asset generation system that produces deployment-ready 3D models from a single image in 30 seconds (or 14 seconds for preview quality), complete with optimized geometry, textures, and polygon budgets suitable for real-time and mobile rendering. The system prioritizes practical usability and speed over maximum resolution, addressing a gap in current 3D generation tools that often overlook real-world deployment constraints.
