WildGaussians: 3D Gaussian Splatting in the Wild

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00383949" target="_blank" >RIV/68407700:21230/24:00383949 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21730/24:00383949

Result on the web

<a href="https://papers.nips.cc/paper_files/paper/2024/file/25c0fe7b157821dd3140727dc07461da-Paper-Conference.pdf" target="_blank" >https://papers.nips.cc/paper_files/paper/2024/file/25c0fe7b157821dd3140727dc07461da-Paper-Conference.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

WildGaussians: 3D Gaussian Splatting in the Wild

Original language description

While the field of 3D scene reconstruction is dominated by NeRFs due to their pho torealistic quality, 3D Gaussian Splatting (3DGS) has recently emerged, offering similar quality with real-time rendering speeds. However, both methods primarily excel with well-controlled 3D scenes, while in-the-wild data– characterized by oc clusions, dynamic objects, and varying illumination– remains challenging. NeRFs can adapt to such conditions easily through per-image embedding vectors, but 3DGSstruggles due to its explicit representation and lack of shared parameters. To address this, we introduce WildGaussians, a novel approach to handle occlusions and appearance changes with 3DGS. By leveraging robust DINO features and integrating an appearance modeling module within 3DGS, our method achieves state-of-the-art results. We demonstrate that WildGaussians matches the real-time rendering speed of 3DGS while surpassing both 3DGS and NeRF baselines in handling in-the-wild data, all within a simple architectural framework.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GX23-07973X" target="_blank" >GX23-07973X: A Unified 3D Map Representation</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Advances in Neural Information Processing Systems 37 (NeurIPS 2024)

ISBN

9798331314385

ISSN

1049-5258

e-ISSN

1049-5258

Number of pages

18

Pages from-to

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Publisher name

Neural Information Processing Systems Foundation, Inc.

Place of publication

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Event location

Vancouver

Event date

Dec 10, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

001633259400234