Abstract 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 …

The advent of neural 3D Gaussians has recently brought about a revolution in the field of
neural rendering facilitating the generation of high-quality renderings at real-time speeds …

In this paper, we present a novel differentiable point-based rendering framework to achieve
photo-realistic relighting. To make the reconstructed scene relightable, we enhance vanilla …

We propose GS-IR a novel inverse rendering approach based on 3D Gaussian Splatting
(GS) that leverages forward map** volume rendering to achieve photorealistic novel view …

Abstract Neural Radiance Fields (NeRF) have constituted a remarkable breakthrough in
image-based 3D reconstruction. However, their implicit volumetric representations differ …

We present the evaluation methodology datasets and results of the BOP Challenge 2023 the
fifth in a series of public com-petitions organized to capture the state of the art in model …

Reconstruction and intrinsic decomposition of scenes from captured imagery would enable
many applications such as relighting and virtual object insertion. Recent NeRF based …

We present the evaluation methodology, datasets and results of the BOP Challenge 2022,
the fourth in a series of public competitions organized with the goal to capture the status quo …

This work considers gradient-based mesh optimization, where we iteratively optimize for a
3D surface mesh by representing it as the isosurface of a scalar field, an increasingly …

We introduce GoMAvatar a novel approach for real-time memory-efficient high-quality
animatable human modeling. GoMAvatar takes as input a single monocular video to create …