Large Reconstruction Model

Large Reconstruction Models (LRMs) aim to efficiently and accurately reconstruct 3D scenes or objects from images, often leveraging transformer-based architectures and neural radiance fields (NeRFs). Current research focuses on improving LRM generalization across diverse scenes and viewpoints, exploring training strategies using both synthetic and real-world data, and enhancing reconstruction quality through techniques like multi-view consistency and geometry/texture refinement. These advancements have significant implications for various applications, including virtual reality, robotics, and 3D content creation, by enabling faster and more robust 3D modeling from various image sources.