Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Guillermo Garcia-Hernando"'
Autor:
Eduardo Arnold, Jamie Wynn, Sara Vicente, Guillermo Garcia-Hernando, Áron Monszpart, Victor Prisacariu, Daniyar Turmukhambetov, Eric Brachmann
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031197680
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::638bf88d149014867e3170feb0b0c65b
https://doi.org/10.1007/978-3-031-19769-7_40
https://doi.org/10.1007/978-3-031-19769-7_40
Publikováno v:
3DV
Most successful approaches to estimate the 6D pose of an object typically train a neural network by supervising the learning with annotated poses in real world images. These annotations are generally expensive to obtain and a common workaround is to
Publikováno v:
IROS
In this work, we explore how a strategic selection of camera movements can facilitate the task of 6D multi-object pose estimation in cluttered scenarios while respecting real-world constraints such as time and distance travelled, important in robotic
Publikováno v:
IROS
Dexterous manipulation of objects in virtual environments with our bare hands, by using only a depth sensor and a state-of-the-art 3D hand pose estimator (HPE), is challenging. While virtual environments are ruled by physics, e.g. object weights and
Autor:
Shreyas Hampali, Fu Xiong, Shipeng Xie, Zdenek Krnoul, Weiguo Zhou, Sijia Mei, Seungryul Baek, Zhaohui Zhang, Haifeng Sun, Guillermo Garcia-Hernando, Yang Xiao, Dongheui Lee, Angela Yao, Umar Iqbal, Mahdi Rad, Marek Hrúz, Adrian Spurr, Qingfu Wan, Zhiguo Cao, Junsong Yuan, Vincent Lepetit, Pavlo Molchanov, Romain Brégier, Pengfei Ren, Yunhui Liu, Shile Li, Philippe Weinzaepfel, Linlin Yang, Anil Armagan, Weiting Huang, Grégory Rogez, Boshen Zhang, Tae-Kyun Kim, Mingxiu Chen, Jakub Kanis
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585914
ECCV (23)
ECCV (23)
We study how well different types of approaches generalise in the task of 3D hand pose estimation under single hand scenarios and hand-object interaction. We show that the accuracy of state-of-the-art methods can drop, and that they fail mostly on po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::334571a0b2fa3856d677209cb23e6322
Object pose recovery has gained increasing attention in the computer vision field as it has become an important problem in rapidly evolving technological areas related to autonomous driving, robotics, and augmented reality. Existing review-related st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2be64d657e79ae969e992626ebf4e03e
Autor:
Gabriel J. Brostow, Daniyar Turmukhambetov, Danail Stoyanov, Anita Rau, Guillermo Garcia-Hernando
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585570
ECCV (5)
ECCV (5)
To what extent are two images picturing the same 3D surfaces? Even when this is a known scene, the answer typically requires an expensive search across scale space, with matching and geometric verification of large sets of local features. This expens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a17228180f6f330abdb8d0fba1f99998
https://doi.org/10.1007/978-3-030-58558-7_37
https://doi.org/10.1007/978-3-030-58558-7_37
Publikováno v:
Machine Vision and Applications. 29:207-217
While action recognition has become an important line of research in computer vision, the recognition of particular events such as aggressive behaviors, or fights, has been relatively less studied. These tasks may be exceedingly useful in some video
Publikováno v:
RGB-D Image Analysis and Processing ISBN: 9783030286026
Interest in estimating the 6D pose, i.e. 3D locations and rotations, of an object of interest has emerged since its promising applications in fields such as robotics and augmented reality. To recover poses from objects that have been seen in advance,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::795dd7628460b3fae9febd07a400b8ae
https://doi.org/10.1007/978-3-030-28603-3_11
https://doi.org/10.1007/978-3-030-28603-3_11