activity
20162026
most citedReconFusion: 3D Reconstruction with Diffusion Priors

20 citations · 72 across the 25 of their papers we have counts for

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Showing 2023Show all

8 papers · 1 filter

cs.CV2023★ 1 cited

Nuvo: Neural UV Mapping for Unruly 3D Representations

Pratul P. Srinivasan, Stephan J. Garbin, Dor Verbin +2

Existing UV mapping algorithms are designed to operate on well-behaved meshes, instead of the geometry representations produced by state-of-the-art 3D reconstruction and generation…

cs.CV2023★ 20 cited

ReconFusion: 3D Reconstruction with Diffusion Priors

Rundi Wu, Ben Mildenhall, Philipp Henzler +8

3D reconstruction methods such as Neural Radiance Fields (NeRFs) excel at rendering photorealistic novel views of complex scenes. However, recovering a high-quality NeRF typically…

cs.CV2023

Generative Powers of Ten

Xiaojuan Wang, Janne Kontkanen, Brian Curless +6

We present a method that uses a text-to-image model to generate consistent content across multiple image scales, enabling extreme semantic zooms into a scene, e.g., ranging from a…

cs.CV2023★ 1 cited

Eclipse: Disambiguating Illumination and Materials using Unintended Shadows

Dor Verbin, Ben Mildenhall, Peter Hedman +3

Decomposing an object's appearance into representations of its materials and the surrounding illumination is difficult, even when the object's 3D shape is known beforehand. This pr…

cs.CV2023★ 14 cited

Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields

Jonathan T. Barron, Ben Mildenhall, Dor Verbin +2

Neural Radiance Field training can be accelerated through the use of grid-based representations in NeRF's learned mapping from spatial coordinates to colors and volumetric density.…

cs.CV2023

Neural Microfacet Fields for Inverse Rendering

Alexander Mai, Dor Verbin, Falko Kuester +1

We present Neural Microfacet Fields, a method for recovering materials, geometry, and environment illumination from images of a scene. Our method uses a microfacet reflectance mode…

cs.CV2023★ 4 cited

MERF: Memory-Efficient Radiance Fields for Real-time View Synthesis in Unbounded Scenes

Christian Reiser, Richard Szeliski, Dor Verbin +5

Neural radiance fields enable state-of-the-art photorealistic view synthesis. However, existing radiance field representations are either too compute-intensive for real-time render…

cs.CV2023★ 3 cited

BakedSDF: Meshing Neural SDFs for Real-Time View Synthesis

Lior Yariv, Peter Hedman, Christian Reiser +5

We present a method for reconstructing high-quality meshes of large unbounded real-world scenes suitable for photorealistic novel view synthesis. We first optimize a hybrid neural…