Zobrazeno 1 - 10
of 100
pro vyhledávání: '"Siddhartha Chaudhuri"'
Publikováno v:
Acta Crystallographica Section E, Vol 70, Iss 6, Pp m236-m236 (2014)
In the title compound, [Co(NCS)2(C6H6N2O)2(H2O)2], the CoII cation is located on an inversion centre and is coordinated by two thiocyanate anions, two nicotinamide molecules and two water molecules in a distorted N2O2S2 octahedral geometry. The amide
Externí odkaz:
https://doaj.org/article/991ea88a886b4c3e9271b4453cc9c8f1
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics. 28:4032-4047
Humans routinely sit or lean against supporting surfaces and it is important to shape these surfaces to be comfortable and ergonomic. We give a method to design the geometric shape of rigid supporting surfaces to maximize the ergonomics of physically
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ea3a5317b1bfb66d034aed1cefd48aa
https://doi.org/10.1109/tvcg.2021.3112127
https://doi.org/10.1109/tvcg.2021.3112127
Publikováno v:
Computer Graphics Forum. 39:643-666
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b40eb415f931c47b2699b8b013a1068
https://doi.org/10.1111/cgf.14020
https://doi.org/10.1111/cgf.14020
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200618
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf7917a30d5302d3861e4e3ea4894590
https://doi.org/10.1007/978-3-031-20062-5_35
https://doi.org/10.1007/978-3-031-20062-5_35
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200618
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91ee5a5fe4caebd61077f889e38734bb
https://doi.org/10.1007/978-3-031-20062-5_29
https://doi.org/10.1007/978-3-031-20062-5_29
Publikováno v:
IEEE transactions on visualization and computer graphics.
Humans routinely sit or lean against supporting surfaces and it is important to shape these surfaces to be comfortable and ergonomic. We give a method to design the geometric shape of rigid supporting surfaces to maximize the ergonomics of physically
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::8cf8ec7fcca982161aabc79e54590d30
https://pubmed.ncbi.nlm.nih.gov/34520357
https://pubmed.ncbi.nlm.nih.gov/34520357
Publikováno v:
CVPR
We introduce a deep generative network for 3D shape detailization, akin to stylization with the style being geometric details. We address the challenge of creating large varieties of high-resolution and detailed 3D geometry from a small set of exempl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39e09a52d95ca0bcf872d83286b20566
https://doi.org/10.1109/cvpr46437.2021.01548
https://doi.org/10.1109/cvpr46437.2021.01548
Autor:
Noam Aigerman, Mikaela Angelina Uy, Leonidas J. Guibas, Vladimir G. Kim, Siddhartha Chaudhuri, Minhyuk Sung
Publikováno v:
CVPR
We propose a novel technique for producing high-quality 3D models that match a given target object image or scan. Our method is based on retrieving an existing shape from a database of 3D models and then deforming its parts to match the target shape.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c80bc07f5a9f328303606ad551cd9997
https://doi.org/10.1109/cvpr46437.2021.01154
https://doi.org/10.1109/cvpr46437.2021.01154
Publikováno v:
ACM Transactions on Graphics. 37:1-14
We introduce SCORES, a recursive neural network for shape composition. Our network takes as input sets of parts from two or more source 3D shapes and a rough initial placement of the parts. It outputs an optimized part structure for the composed shap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6744d5f6730243ec244bc0b3621838b1
https://doi.org/10.1145/3272127.3275008
https://doi.org/10.1145/3272127.3275008
Autor:
Sanjeev Muralikrishnan, Siddhartha Chaudhuri, Noam Aigerman, Vladimir G. Kim, Matthew Fisher, Niloy J. Mitra
We investigate the problem of training generative models on a very sparse collection of 3D models. We use geometrically motivated energies to augment and thus boost a sparse collection of example (training) models. We analyze the Hessian of the as-ri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::800e19de1cc919c08ef196bd87b7bcb0