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20232026
most citedReconFusion: 3D Reconstruction with Diffusion Priors

20 citations · 33 across the 15 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024

Can Generative Video Models Help Pose Estimation?

Ruojin Cai, Jason Y. Zhang, Philipp Henzler +3

Pairwise pose estimation from images with little or no overlap is an open challenge in computer vision. Existing methods, even those trained on large-scale datasets, struggle in th…

cs.CV2024

Generative Multiview Relighting for 3D Reconstruction under Extreme Illumination Variation

Hadi Alzayer, Philipp Henzler, Jonathan T. Barron +3

Reconstructing the geometry and appearance of objects from photographs taken in different environments is difficult as the illumination and therefore the object appearance vary acr…

cs.CV2024

SimVS: Simulating World Inconsistencies for Robust View Synthesis

Alex Trevithick, Roni Paiss, Philipp Henzler +9

Novel-view synthesis techniques achieve impressive results for static scenes but struggle when faced with the inconsistencies inherent to casual capture settings: varying illuminat…

cs.CV2024★ 1 cited

IllumiNeRF: 3D Relighting Without Inverse Rendering

Xiaoming Zhao, Pratul P. Srinivasan, Dor Verbin +3

Existing methods for relightable view synthesis -- using a set of images of an object under unknown lighting to recover a 3D representation that can be rendered from novel viewpoin…

cs.CV2024★ 11 cited

CAT3D: Create Anything in 3D with Multi-View Diffusion Models

Ruiqi Gao, Aleksander Holynski, Philipp Henzler +5

Advances in 3D reconstruction have enabled high-quality 3D capture, but require a user to collect hundreds to thousands of images to create a 3D scene. We present CAT3D, a method f…