Güler, RA;
Kokkinos, I;
(2019)
HoloPose: Holistic 3D Human Reconstruction In-The-Wild.
In:
(Proceedings) CVPR 2019 - IEEE Conference on Computer Vision and Pattern Recognition.
(pp. pp. 10884-10894).
Computer Vision Foundation / IEEE: Long Beach, CA, USA.
(In press).
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Abstract
We introduce HoloPose, a method for holistic monocular 3D human body reconstruction. We first introduce a part-based model for 3D model parameter regression that allows our method to operate in-the-wild, gracefully handling severe occlusions and large pose variation. We further train a multi-task network comprising 2D, 3D and Dense Pose estimation to drive the 3D reconstruction task. For this we introduce an iterative refinement method that aligns the model-based 3D estimates of 2D/3D joint positions and DensePose with their image-based counterparts delivered by CNNs, achieving both model-based, global consistency and high spatial accuracy thanks to the bottom-up CNN processing. We validate our contributions on challenging benchmarks, showing that our method allows us to get both accurate joint and 3D surface estimates, while operating at more than 10fps in-the-wild. More information about our approach, including videos and demos is available at http://arielai.com/holopose.
| Type: | Proceedings paper |
|---|---|
| Title: | HoloPose: Holistic 3D Human Reconstruction In-The-Wild. |
| Event: | CVPR 2019 - IEEE Conference on Computer Vision and Pattern Recognition |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | http://openaccess.thecvf.com/CVPR2019.py |
| 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. |
| 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/10088677 |
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