We present Stable Virtual Camera (Seva), a generalist diffusion model that creates novel views of a scene, given any number of input views and target cameras. Existing works …
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 …
We present Stable Video 3D (SV3D) - a latent video diffusion model for high-resolution, image-to-multi-view generation of orbital videos around a 3D object. Recent work on 3D …
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. …
It is now my third time writing a summary of NeRFy things at a conference. This time it is the big one: CVPR. The list of accepted papers is massive again, with 2359 papers.
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 …
Substandard and falsified medicines present a serious threat to public health. Simple, low-cost screening tools are important in the identification of such products in low- and …