Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Thibault Groueix"'
Autor:
Fabien Baradel, Romain Bregier, Thibault Groueix, Philippe Weinzaepfel, Yannis Kalantidis, Gregory Rogez
Training state-of-the-art models for human pose estimation in videos requires datasets with annotations that are really hard and expensive to obtain. Although transformers have been recently utilized for body pose sequence modeling, related methods r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35b349aed332e80cbff64a202d5605ca
Autor:
Fabien Baradel, Thibault Groueix, Philippe Weinzaepfel, Romain Bregier, Yannis Kalantidis, Gregory Rogez
Training state-of-the-art models for human body pose and shape recovery from images or videos requires datasets with corresponding annotations that are really hard and expensive to obtain. Our goal in this paper is to study whether poses from 3D Moti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b9694258d238fdc32c5eaf7b234c8fa
http://arxiv.org/abs/2110.09243
http://arxiv.org/abs/2110.09243
Publikováno v:
Computer Graphics Forum
Computer Graphics Forum, Wiley, 2019, 38 (5), pp.123-133. ⟨10.1111/cgf.13794⟩
Computer Graphics Forum, Wiley, 2019, 38 (5), pp.123-133. ⟨10.1111/cgf.13794⟩
International audience; We propose a self-supervised approach to deep surface deformation. Given a pair of shapes, our algorithm directly predicts a parametric transformation from one shape to the other respecting correspondences. Our insight is to u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3be7e49ba927a9104e251fb4c269617
https://hal-enpc.archives-ouvertes.fr/hal-02178969
https://hal-enpc.archives-ouvertes.fr/hal-02178969
Autor:
Tae-Kyun Kim, Tomas Hodan, Ales Leonardis, Bertram Drost, Rigas Kouskouridas, Carsten Rother, Vincent Lepetit, Carsten Steger, Federico Tombari, Frank Michel, Krzysztof Walas, Caner Sahin, Jiri Matas, Thibault Groueix, Kostas E. Bekris
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030110086
ECCV Workshops (1)
ECCV Workshops (1)
This document summarizes the 4th International Workshop on Recovering 6D Object Pose which was organized in conjunction with ECCV 2018 in Munich. The workshop featured four invited talks, oral and poster presentations of accepted workshop papers, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::941a0076f5e94baba6d1cbaca31098a6
https://doi.org/10.1007/978-3-030-11009-3_36
https://doi.org/10.1007/978-3-030-11009-3_36
Publikováno v:
ECCV 2018
ECCV 2018, Sep 2018, Munich, Germany
Computer Vision – ECCV 2018 ISBN: 9783030012151
ECCV (2)
ECCV 2018, Sep 2018, Munich, Germany
Computer Vision – ECCV 2018 ISBN: 9783030012151
ECCV (2)
International audience; We present a new deep learning approach for matching deformable shapes by introducing Shape Deformation Networks which jointly encode 3D shapes and correspondences. This is achieved by factoring the surface representation into
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64ba09ef0c15005ea7bb6d724df69bde
https://hal.archives-ouvertes.fr/hal-01830474
https://hal.archives-ouvertes.fr/hal-01830474
Publikováno v:
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
We introduce a method for learning to generate the surface of 3D shapes. Our approach represents a 3D shape as a collection of parametric surface elements and, in contrast to methods generating voxel grids or point clouds, naturally infers a surface
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c87afcb6e227376792bb71a0873f63f
https://doi.org/10.1109/cvpr.2018.00030
https://doi.org/10.1109/cvpr.2018.00030
Publikováno v:
ACM Transactions on Computer-Human Interaction (TOCHI); Oct2024, Vol. 31 Issue 5, p1-41, 41p
Publikováno v:
ACM Transactions on Graphics; Oct2024, Vol. 43 Issue 5, p1-20, 20p
Publikováno v:
ACM Transactions on Graphics; Apr2024, Vol. 43 Issue 2, p1-18, 18p
Publikováno v:
ACM Transactions on Sensor Networks; Mar2024, Vol. 20 Issue 2, p1-21, 21p