Results 31 to 40 of about 14,095 (277)

Global Structure-From-Motion Enhanced Neural Radiance Fields 3D Reconstruction [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Urban three-dimensional modeling involves digitizing geographical elements such as urban ground and architecture, profoundly impacting urban management, planning, and development.
T. Ye, H. Huang, Y. Liu, J. Yang
doaj   +1 more source

NEURAL RADIANCE FIELDS (NERF): REVIEW AND POTENTIAL APPLICATIONS TO DIGITAL CULTURAL HERITAGE [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023
Neural Radiance Fields (NeRF or NeRFs) are to date emerging as a novel method for synthesizing novel views of complex 3D scenes, leveraging an artificial neural network to optimize a volumetric scene function using a set of input views.
V. Croce, G. Caroti, L. De Luca, A. Piemonte, P. Véron   +4 more
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Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches [PDF]

, 2012
Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in hundreds or thousands of spectral channels with higher spectral resolution than multispectral cameras.
Antonio Plaza, Jocelyn Chanussot, José M. Bioucas-dias, Mario Parente, Nicolas Dobigeon, Paul Gader, Qian Du, Senior Member, Senior Member   +8 more
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Effects of integration time on in-water radiometric profiles [PDF]

, 2018
This work investigates the effects of integration time on in-water downward irradiance E-d, upward irradiance E-u and upwelling radiance L-u profile data acquired with free-fall hyperspectral systems.
Antoine, Bohren, BulgarelliZibordi, Chandrasekhar, Clark, Davide D’Alimonte, DeGroot, D’Alimonte, D’Alimonte, D’Alimonte, D’Alimonte, D’Alimonte, Elfouhaily, Emde, Escher, Fournier, Fournier, Franz, Giuseppe Zibordi, Hansen, Hieronymi, Hieronymi, Hieronymi, Hieronymi, Hieronymi, Hooker, Jerlov, Jones, Kajiyama, Kajiyama, KajiyamaSato, KajiyamaWyrzykowski, Mobley, Mueller, Penndorf, Sathyendranath, Schattschneider, Seber, Siegel, Smith, Sobolev, Tamito Kajiyama, Tsai, Van De Hulst, Werdell, You, Zaneveld, Zibordi, Zibordi, Zibordi, Zibordi   +50 more
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MarkNerf:Watermarking for Neural Radiance Field

, 2023
A watermarking algorithm is proposed in this paper to address the copyright protection issue of implicit 3D models. The algorithm involves embedding watermarks into the images in the training set through an embedding network, and subsequently utilizing the NeRF model for 3D modeling.
Chen, Lifeng, Liu, Jia, Ke, Yan, Sun, Wenquan, Dong, Weina, Pan, Xiaozhong   +5 more
openaire   +2 more sources

Appearance Enhancement and Semantic Segmentation-based Neural Radiance Fields [PDF]

Jisuanji kexue
The accelerated advancement of deep learning has notably propelled 3D reconstruction techniques within the field of computer vision.NeRFs have become an essential methodology due to their adeptness at scene modeling and superior view synthesis.However ...
CAO Mingwei, HUANG Baolong, ZHAO Haifeng
doaj   +1 more source

Self-Evolving Neural Radiance Fields

, 2023
Recently, neural radiance field (NeRF) has shown remarkable performance in novel view synthesis and 3D reconstruction. However, it still requires abundant high-quality images, limiting its applicability in real-world scenarios. To overcome this limitation, recent works have focused on training NeRF only with sparse viewpoints by giving additional ...
Jung, Jaewoo, Han, Jisang, Kang, Jiwon, Kim, Seongchan, Kwak, Min-Seop, Kim, Seungryong   +5 more
openaire   +2 more sources

PyNeRF: Pyramidal Neural Radiance Fields

, 2023
Neural Radiance Fields (NeRFs) can be dramatically accelerated by spatial grid representations. However, they do not explicitly reason about scale and so introduce aliasing artifacts when reconstructing scenes captured at different camera distances. Mip-NeRF and its extensions propose scale-aware renderers that project volumetric frustums rather than ...
Turki, Haithem, Zollhöfer, Michael, Richardt, Christian, Ramanan, Deva   +3 more
openaire   +2 more sources

Generative Neural Articulated Radiance Fields

, 2022
Unsupervised learning of 3D-aware generative adversarial networks (GANs) using only collections of single-view 2D photographs has very recently made much progress. These 3D GANs, however, have not been demonstrated for human bodies and the generated radiance fields of existing frameworks are not directly editable, limiting their applicability in ...
Bergman, Alexander W. (author), Kellnhofer, P. (author), Yifan, Wang (author), Chan, Eric R. (author), Lindell, David B. (author), Wetzstein, Gordon (author)   +5 more
openaire   +3 more sources

A nanoflare model for active region radiance: application of artificial neural networks

, 2008
Context. Nanoflares are small impulsive bursts of energy that blend with and possibly make up much of the solar background emission. Determining their frequency and energy input is central to understanding the heating of the solar corona.
Andreon, Aschwanden, Aschwanden, Ball, Bazarghan, Cargill, Cortiglioni, D. E. Innes, E. Karami, H. Safari, Hudson, Levine, Lin, M. Bazarghan, Parker, Parker, Parzen, Patsourakos, Pauluhn, S. K. Solanki, Shimizu, Sodre, Specht, Specht, von Hippel, Wang, Warren, Wilhelm, Wilhelm, Zirker   +29 more
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