Kulon, D;
Güler, RA;
Kokkinos, I;
Bronstein, M;
Zafeiriou, S;
(2020)
Weakly-supervised mesh-convolutional hand reconstruction in the wild.
In:
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
(pp. pp. 4989-4999).
IEEE: Seattle, WA, USA, USA.
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Abstract
We introduce a simple and effective network architecture for monocular 3D hand pose estimation consisting of an image encoder followed by a mesh convolutional decoder that is trained through a direct 3D hand mesh reconstruction loss. We train our network by gathering a large-scale dataset of hand action in YouTube videos and use it as a source of weak supervision. Our weakly-supervised mesh convolutions-based system largely outperforms state-of-the-art methods, even halving the errors on the in the wild benchmark. The dataset and additional resources are available at https://arielai.com/mesh_hands.
| Type: | Proceedings paper |
|---|---|
| Title: | Weakly-supervised mesh-convolutional hand reconstruction in the wild |
| Event: | 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/CVPR42600.2020.00504 |
| Publisher version: | https://doi.org/10.1109/CVPR42600.2020.00504 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Three-dimensional displays, Two dimensional displays, Image reconstruction, Pose estimation, Shape, YouTube, Videos |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10119371 |
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