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20172026
most citedFourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

1.2k citations · 2k across the 43 of their papers we have counts for

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Showing 2023Show all

11 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…

astro-ph.HE2023★ 1 cited

Orbital Polarimetric Tomography of a Flare Near the Sagittarius A* Supermassive Black Hole

Aviad Levis, Andrew A. Chael, Katherine L. Bouman +2

The interaction between the supermassive black hole at the center of the Milky Way, Sagittarius A*, and its accretion disk occasionally produces high-energy flares seen in X-ray, i…

cs.CV2023

Single View Refractive Index Tomography with Neural Fields

Brandon Zhao, Aviad Levis, Liam Connor +2

Refractive Index Tomography is the inverse problem of reconstructing the continuously-varying 3D refractive index in a scene using 2D projected image measurements. Although a purel…

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…