*This seminar was held in-person in Wu and Chen as well as virtually…
Over the past year, the large language model has achieved significant milestones, approaching human-like intelligence across various domains. However, there has been limited investigation into large-scale 3D reconstruction in the literature. In this talk, I will primarily focus on our recent advancements in large-scale 3D reconstruction.
I will start with an introduction to the basics of the Large-scale Reconstruction Model (LRM), aiming to develop a robust and highly generalizable 3D reconstruction system utilizing high-quality 3D data. I will also explain how LRM can be used to efficiently perform high-quality text-to-3D and image-to-3D generation tasks, such as Instant3D and DMV3D.Finally, I will highlight our recent work, specifically our progress in large-scale 3D reconstruction using Gaussian Splatting (GRM). As a large-scale reconstructor, GRM can reconstruct a 3D asset from sparse-view images in about 0.1 seconds. Moreover, GRM shows promising potential in generative tasks, such as text-to-3D and image-to-3D, through its integration with existing multi-view diffusion models.