THOR-Net: End-to-end Graformer-based Realistic Two Hands and Object Reconstruction with Self-supervision-Reference-Cited by-同舟云学术

THOR-Net: End-to-end Graformer-based Realistic Two Hands and Object Reconstruction with Self-supervision

Published:2023-01 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
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Author:

Aboukhadra Ahmed Tawfik¹,Malik Jameel¹,Elhayek Ahmed²,Robertini Nadia¹,Stricker Didier¹

Affiliation:

1. DFKI-AV Kaiserslautern

2. UPM Saudi Arabia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10030081/10030084/10030162.pdf?arnumber=10030162

Reference43 articles.

1. Markus Oberweger, and Vin-cent Lepetit. Honnotate: A method for 3d annotation of hand and object poses;hampali;Computer Vision and Pattern Recognition (CVPR),2020

2. Franziska Mueller, Mohamed Elgharib, and Christian Theobalt. Eventhands: Real-time neural 3d hand pose estimation from an event stream;rudnev;International Conference on Computer Vision (ICCV),2021

3. Surface simplification using quadric error metrics

4. Embodied hands

5. Leveraging Photometric Consistency Over Time for Sparsely Supervised Hand-Object Reconstruction

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