Zobrazeno 1 - 10
of 466
pro vyhledávání: '"Leonidas J Guibas"'
Autor:
Jiahui Huang, Jun Gao, Vignesh Ganapathi-Subramanian, Hao Su, Yin Liu, Chengcheng Tang, Leonidas J. Guibas
Publikováno v:
Computational Visual Media, Vol 4, Iss 4, Pp 385-397 (2018)
Abstract The perception of the visual world through basic building blocks, such as cubes, spheres, and cones, gives human beings a parsimonious understanding of the visual world. Thus, efforts to find primitive-based geometric interpretations of visu
Externí odkaz:
https://doaj.org/article/712691899e18471fba421d995aa4e38c
Publikováno v:
IEEE Robotics and Automation Letters. 7:4845-4852
We describe a method for unpaired realistic depth synthesis that learns diverse variations from the real-world depth scans and ensures geometric consistency between the synthetic and synthesized depth. The synthesized realistic depth can then be used
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2cbafe6d488bb0e33877363274cb3bd7
https://doi.org/10.1109/lra.2022.3148788
https://doi.org/10.1109/lra.2022.3148788
3D indoor scenes are widely used in computer graphics, with applications ranging from interior design to gaming to virtual and augmented reality. They also contain rich information, including room layout, as well as furniture type, geometry, and plac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8387f6fe91c22e1eff7b9714065a88e
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Regressing rotations on SO(3) manifold using deep neural networks is an important yet unsolved problem. The gap between the Euclidean network output space and the non-Euclidean SO(3) manifold imposes a severe challenge for neural network learning in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::06338201c354c6dc5a0b33e1a7f4f725
https://doi.org/10.1109/cvpr52688.2022.00653
https://doi.org/10.1109/cvpr52688.2022.00653
Publikováno v:
Computer Graphics Forum. 39:197-207
We present an approach to inform the reconstruction of a surface from a point scan through topological priors. The reconstruction is based on basis functions which are optimized to provide a good fit to the point scan while satisfying predefined topo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14f846d91808e332136d7d438f55f5a7
https://doi.org/10.1111/cgf.14079
https://doi.org/10.1111/cgf.14079
Publikováno v:
IEEE Robotics and Automation Letters
We propose a new method for segmentation-free joint estimation of orthogonal planes, their intersection lines, relationship graph and corners lying at the intersection of three orthogonal planes. Such unified scene exploration under orthogonality all
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1027bb742976a61844450db978bb38e1
https://doi.org/10.1109/lra.2020.2969936
https://doi.org/10.1109/lra.2020.2969936
D shape generation is a fundamental operation in computer graphics. While significant progress has been made, especially with recent deep generative models, it remains a challenge to synthesize high-quality shapes with rich geometric details and comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::237bb5c7c37d7a6c7052a2c8d748e65b
https://orca.cardiff.ac.uk/id/eprint/149165/1/DSG-Net-TOG2022.pdf
https://orca.cardiff.ac.uk/id/eprint/149165/1/DSG-Net-TOG2022.pdf
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence.
We present SyNoRiM, a novel way to jointly register multiple non-rigid shapes by synchronizing the maps that relate learned functions defined on the point clouds. Even though the ability to process non-rigid shapes is critical in various applications
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18b01367197adc2e587d6c1f34f6166d
https://pubmed.ncbi.nlm.nih.gov/35380953
https://pubmed.ncbi.nlm.nih.gov/35380953
Autor:
Bokui Shen, Zhenyu Jiang, Christopher Choy, Silvio Savarese, Leonidas J. Guibas, Anima Anandkumar, Yuke Zhu
Manipulating volumetric deformable objects in the real world, like plush toys and pizza dough, bring substantial challenges due to infinite shape variations, non-rigid motions, and partial observability. We introduce ACID, an action-conditional visua
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8fac3d3337989b8f08210a80d312ca93
http://arxiv.org/abs/2203.06856
http://arxiv.org/abs/2203.06856
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031198175
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f98e653a3cddc0db39f04fec63fbbeb9
https://doi.org/10.1007/978-3-031-19818-2_6
https://doi.org/10.1007/978-3-031-19818-2_6