Neural Radiance Field (NeRF), a new novel view synthesis with implicit scene
representation has taken the field of Computer Vision by storm. As a novel view synthesis …

Modeling and re-rendering dynamic 3D scenes is a challenging task in 3D vision. Prior
approaches build on NeRF and rely on implicit representations. This is slow since it requires …

In this work, we investigate the problem of creating high-fidelity 3D content from only a single
image. This is inherently challenging: it essentially involves estimating the underlying 3D …

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 …

Abstract Recently 3D Gaussian Splatting has demonstrated impressive novel view synthesis
results reaching high fidelity and efficiency. However strong artifacts can be observed when …

Novel view synthesis with sparse inputs is a challenging problem for neural radiance fields
(NeRF). Recent efforts alleviate this challenge by introducing external supervision, such as …

We introduce MVSplat, an efficient model that, given sparse multi-view images as input,
predicts clean feed-forward 3D Gaussians. To accurately localize the Gaussian centers, we …

We propose SparseFusion, a sparse view 3D reconstruction approach that unifies recent
advances in neural rendering and probabilistic image generation. Existing approaches …

Novel view synthesis from limited observations remains a crucial and ongoing challenge. In
the realm of NeRF-based few-shot view synthesis, there is often a trade-off between the …

In recent years, neural implicit surface reconstruction methods have become popular for
multi-view 3D reconstruction. In contrast to traditional multi-view stereo methods, these …