Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Uday Kusupati"'
Publikováno v:
CVPR
Accurate stereo depth estimation plays a critical role in various 3D tasks in both indoor and outdoor environments. Recently, learning-based multi-view stereo methods have demonstrated competitive performance with limited number of views. However, in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68b79a4dd693f4295e84bc51a7b159fb
http://arxiv.org/abs/1911.10444
http://arxiv.org/abs/1911.10444
Publikováno v:
Computer Vision – ECCV 2018 ISBN: 9783030012397
ECCV (9)
ECCV (9)
3D human pose estimation from a single image is a challenging problem, especially for in-the-wild settings due to the lack of 3D annotated data. We propose two anatomically inspired loss functions and use them with a weakly-supervised learning framew
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a44bc631a1bda545caa729fe10178969
https://doi.org/10.1007/978-3-030-01240-3_41
https://doi.org/10.1007/978-3-030-01240-3_41
Autor:
Yingying Ren, Uday Kusupati, Julian Panetta, Florin Isvoranu, Davide Pellis, Tian Chen, Mark Pauly
We present a computational inverse design framework for a new class of volumetric deployable structures that have compact rest states and deploy into bending-active 3D target surfaces. Umbrella meshes consist of elastic beams, rigid plates, and hinge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af06eda0d4d0840d164d46db9766dc7d
https://infoscience.epfl.ch/record/296487
https://infoscience.epfl.ch/record/296487