Facial De-occlusion Network for Virtual Telepresence Systems
Abstract
To see what is not in the image is one of the broader missions of computer vision. Technology to inpaint images has made significant progress with the coming of deep learning. This paper proposes a method to tackle occlusion specific to human faces. Virtual presence is a promising direction in communication and recreation for the future. However, Virtual Reality (VR) headsets occlude a significant portion of the face, hindering the photo-realistic appearance of the face in the virtual world. State-of-the-art image inpainting methods for de-occluding the eye region does not give usable results. To this end, we propose a working solution that gives usable results to tackle this problem enabling the use of the real-time photo-realistic de-occluded face of the user in VR settings.
Cite
@article{arxiv.2210.12622,
title = {Facial De-occlusion Network for Virtual Telepresence Systems},
author = {Surabhi Gupta and Ashwath Shetty and Avinash Sharma},
journal= {arXiv preprint arXiv:2210.12622},
year = {2022}
}
Comments
This workshop paper is presented in CVPR Workshop on Computer Vision for Augmented and Virtual Reality, New Orleans, LA, 2022. Link: https://xr.cornell.edu/workshop/2022/papers