Zobrazeno 1 - 10
of 3 207
pro vyhledávání: '"Marschner P"'
Autor:
Li, Zixuan, Shen, Pengfei, Sun, Hanxiao, Zhang, Zibo, Guo, Yu, Liu, Ligang, Yan, Ling-Qi, Marschner, Steve, Hasan, Milos, Wang, Beibei
Accurately rendering the appearance of fabrics is challenging, due to their complex 3D microstructures and specialized optical properties. If we model the geometry and optics of fabrics down to the fiber level, we can achieve unprecedented rendering
Externí odkaz:
http://arxiv.org/abs/2409.06368
Autor:
Hassena, Gemmechu, Moon, Jonathan, Fujii, Ryan, Yuen, Andrew, Snavely, Noah, Marschner, Steve, Hariharan, Bharath
Implicit neural fields have made remarkable progress in reconstructing 3D surfaces from multiple images; however, they encounter challenges when it comes to separating individual objects within a scene. Previous work has attempted to tackle this prob
Externí odkaz:
http://arxiv.org/abs/2407.19108
We present a simple algorithm for differentiable rendering of surfaces represented by Signed Distance Fields (SDF), which makes it easy to integrate rendering into gradient-based optimization pipelines. To tackle visibility-related derivatives that m
Externí odkaz:
http://arxiv.org/abs/2405.08733
Rendering volumetric scattering media, including clouds, fog, smoke, and other complex materials, is crucial for realism in computer graphics. Traditional path tracing, while unbiased, requires many long path samples to converge in scenes with scatte
Externí odkaz:
http://arxiv.org/abs/2404.11894
Autor:
Huang, Po-Han, Chen, Shiqian, Hartwig, Oliver, Marschner, David E., Duesberg, Georg S., Stemme, Göran, Li, Jiantong, Gylfason, Kristinn B., Niklaus, Frank
Hierarchical structures are abundant in nature, such as in the superhydrophobic surfaces of lotus leaves and the structural coloration of butterfly wings. They consist of ordered features across multiple size scales, and their unique properties have
Externí odkaz:
http://arxiv.org/abs/2403.17102
Neural fields have become widely used in various fields, from shape representation to neural rendering, and for solving partial differential equations (PDEs). With the advent of hybrid neural field representations like Instant NGP that leverage small
Externí odkaz:
http://arxiv.org/abs/2312.05984
Autor:
Daniel McIntyre, Desi Quintans, Samia Kazi, Haeri Min, Wen-Qiang He, Simone Marschner, Rohan Khera, Natasha Nassar, Clara K. Chow
Publikováno v:
BMC Health Services Research, Vol 24, Iss 1, Pp 1-9 (2024)
Abstract Background Healthcare policy implemented during the COVID-19 pandemic may have impacted the health of patients with heart failure. Australian data provide a unique opportunity to examine service disruption independent of significant COVID-19
Externí odkaz:
https://doaj.org/article/68306260d5da4a51a37b3c8cfc16e754
Autor:
Hendrik Ballhausen, Stefanie Corradini, Claus Belka, Dan Bogdanov, Luca Boldrini, Francesco Bono, Christian Goelz, Guillaume Landry, Giulia Panza, Katia Parodi, Riivo Talviste, Huong Elena Tran, Maria Antonietta Gambacorta, Sebastian Marschner
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-12 (2024)
Abstract In multicentric studies, data sharing between institutions might negatively impact patient privacy or data security. An alternative is federated analysis by secure multiparty computation. This pilot study demonstrates an architecture and imp
Externí odkaz:
https://doaj.org/article/5aa51af602e6467fa4c367b577c04a28
Autor:
Emmanuel Abban-Baidoo, Delphine Manka’abusi, Lenin Apuri, Bernd Marschner, Kwame Agyei Frimpong
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract This study investigated the effects of corn cob biochar (CCB) and rice husk biochar (RHB) additions (at 0%, 5%, and 10% w/w) on nitrogen and carbon dynamics during co-composting with poultry litter, rice straw, and domestic bio-waste. The st
Externí odkaz:
https://doaj.org/article/1e4e3f111be747a39bdd1bfe8bca2593
Autor:
Laura Isigkeit, Tim Hörmann, Espen Schallmayer, Katharina Scholz, Felix F. Lillich, Johanna H. M. Ehrler, Benedikt Hufnagel, Jasmin Büchner, Julian A. Marschner, Jörg Pabel, Ewgenij Proschak, Daniel Merk
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-14 (2024)
Abstract Generative deep learning models enable data-driven de novo design of molecules with tailored features. Chemical language models (CLM) trained on string representations of molecules such as SMILES have been successfully employed to design new
Externí odkaz:
https://doaj.org/article/18a8f717a7c64c0f81f6b3644f448ee3