We study the problem of single-image 3D object reconstruction. Recent works have diverged into two directions: regression-based modeling and generative modeling. Regression methods …
We present SF3D, a novel method for rapid and high-quality textured mesh reconstruction from a single image. Utilizing the Large Reconstruction Model (LRM) as its foundation, SF3D …
Current 3D content generation builds on generative models that output RGB images. Modern graphics pipelines, however, require physically-based rendering (PBR) material properties. …
We present SHINOBI, an end-to-end framework for the reconstruction of shape, material, and illumination from object images captured with varying lighting, pose, and background. …
Asset production in the game industry is time-consuming, and since "The Vanishing of Ethan Carter" photogrammetry has gained traction. While the asset produced by photogrammetry …
Creating relightable objects from images or collections is a fundamental challenge in computer vision and graphics. This problem is also known as inverse rendering. One of the main …
Inverse rendering of an object under entirely unknown capture conditions is a fundamental challenge in computer vision and graphics. Neural approaches such as NeRF have achieved …
In this talk, I will present our recent work on decomposing an object into its shape, reflectance, and illumination. This highly ill-posed problem is inherently more challenging …
Decomposing a scene into its shape, reflectance and illumination is a fundamental problem in computer vision and graphics. Neural approaches such as NeRF have achieved remarkable …
Decomposing a scene into its shape, reflectance, and illumination is a challenging but important problem in computer vision and graphics. This problem is inherently more …