Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Leonid Pishchulin"'
Publikováno v:
CVPR
We consider the task of 3D pose estimation and tracking of multiple people seen in an arbitrary number of camera feeds. We propose TesseTrack1, a novel top-down approach that simultaneously reasons about multiple individuals’ 3D body joint reconstr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1438274140d07ac3c901cd9f9cbfe40
https://doi.org/10.1109/cvpr46437.2021.01494
https://doi.org/10.1109/cvpr46437.2021.01494
Publikováno v:
CVPR
Neural architecture search (NAS) approaches aim at automatically finding novel CNN architectures that fit computational constraints while maintaining a good performance on the target platform. We introduce a novel efficient one-shot NAS approach to o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e15ddcc152d7135354c5b7142a386442
https://lirias.kuleuven.be/handle/123456789/652121
https://lirias.kuleuven.be/handle/123456789/652121
Publikováno v:
Pattern Recognition
Pattern Recognition, Elsevier, 2017, 67, pp.276-286. ⟨10.1016/j.patcog.2017.02.018⟩
Pattern Recognition, 2017, 67, pp.276-286. ⟨10.1016/j.patcog.2017.02.018⟩
Pattern Recognition, Elsevier, 2017, 67, pp.276-286. ⟨10.1016/j.patcog.2017.02.018⟩
Pattern Recognition, 2017, 67, pp.276-286. ⟨10.1016/j.patcog.2017.02.018⟩
Statistical models of 3D human shape and pose learned from scan databases have developed into valuable tools to solve a variety of vision and graphics problems. Unfortunately, most publicly available models are of limited expressiveness as they were
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e63e3e452d491e1f1a32657f738fa80a
https://doi.org/10.1016/j.patcog.2017.02.018
https://doi.org/10.1016/j.patcog.2017.02.018
Autor:
Christian Theobalt, Bernt Schiele, Ahmed Elhayek, Mykhaylo Andriluka, C. Bregler, Arjun Jain, Leonid Pishchulin, E. de Aguiar, J. Thompson
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 39:501-514
Marker-less motion capture has seen great progress, but most state-of-the-art approaches fail to reliably track articulated human body motion with a very low number of cameras, let alone when applied in outdoor scenes with general background. In this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f830b23f8ce947229886fe07c5392bab
https://doi.org/10.1109/tpami.2016.2557779
https://doi.org/10.1109/tpami.2016.2557779
Publikováno v:
CVPR Workshops
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops
Multi-person pose estimation in images and videos is an important yet challenging task with many applications. Despite the large improvements in human pose estimation enabled by the development of convolutional neural networks, there still exist a lo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f13eb6adc6b6a1fd821ea503d01c5b2
https://doi.org/10.1109/cvprw.2018.00058
https://doi.org/10.1109/cvprw.2018.00058
Autor:
Evgeny Levinkov, Bernt Schiele, Leonid Pishchulin, Mykhaylo Andriluka, Bjoern Andres, Siyu Tang, Eldar Insafutdinov
Publikováno v:
CVPR
In this paper we propose an approach for articulated tracking of multiple people in unconstrained videos. Our starting point is a model that resembles existing architectures for single-frame pose estimation but is substantially faster. We achieve thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7dc5072cbd686880fc23281a9606628a
https://doi.org/10.1109/cvpr.2017.142
https://doi.org/10.1109/cvpr.2017.142
Publikováno v:
Computer Vision – ECCV 2016 ISBN: 9783319464657
ECCV (6)
ECCV (6)
The goal of this paper is to advance the state-of-the-art of articulated pose estimation in scenes with multiple people. To that end we contribute on three fronts. We propose (1) improved body part detectors that generate effective bottom-up proposal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3fdf9d7f4ba01bcbd773890990a156ba
https://doi.org/10.1007/978-3-319-46466-4_3
https://doi.org/10.1007/978-3-319-46466-4_3
Publikováno v:
Pattern Recognition. 45:3131-3140
This paper systematically analyzes the strengths and weaknesses of existing image warping algorithms on the tasks of face recognition. Image warping is used to cope with local and global image variability and in general is an NP-complete problem. Alt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d93690ef1710e4d981052e2076c95b6
https://doi.org/10.1016/j.patcog.2011.10.017
https://doi.org/10.1016/j.patcog.2011.10.017
Autor:
Siyu Tang, Bjoern Andres, Peter V. Gehler, Mykhaylo Andriluka, Leonid Pishchulin, Bernt Schiele, Eldar Insafutdinov
Publikováno v:
CVPR
This paper considers the task of articulated human pose estimation of multiple people in real world images. We propose an approach that jointly solves the tasks of detection and pose estimation: it infers the number of persons in a scene, identifies
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7142e3b5db79ff7e2ea2f987fbaaeda7
http://arxiv.org/abs/1511.06645
http://arxiv.org/abs/1511.06645
Autor:
Arjun Jain, E. de Aguiar, Christian Theobalt, Ahmed Elhayek, Mykhaylo Andriluka, Bernt Schiele, Chris Bregler, Jonathan Tompson, Leonid Pishchulin
Publikováno v:
CVPR
We present a novel method for accurate marker-less capture of articulated skeleton motion of several subjects in general scenes, indoors and outdoors, even from input filmed with as few as two cameras. Our approach unites a discriminative image-based
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2cbe5b38fba0f2a4b7c650e4dc906a27
https://doi.org/10.1109/cvpr.2015.7299005
https://doi.org/10.1109/cvpr.2015.7299005