Attention based Occlusion Removal for Hybrid Telepresence Systems

• URL: http://arxiv.org/abs/2112.01098v1
• Date: Thu, 2 Dec 2021 10:18:22 GMT
• Title: Attention based Occlusion Removal for Hybrid Telepresence Systems
• Authors: Surabhi Gupta, Ashwath Shetty, Avinash Sharma
• Abstract summary: We propose a novel attention-enabled encoder-decoder architecture for HMD de-occlusion. We report superior qualitative and quantitative results over state-of-the-art methods. We also present applications of this approach to hybrid video teleconferencing using existing animation and 3D face reconstruction pipelines.
• Score: 5.006086647446482
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Traditionally, video conferencing is a widely adopted solution for telecommunication, but a lack of immersiveness comes inherently due to the 2D nature of facial representation. The integration of Virtual Reality (VR) in a communication/telepresence system through Head Mounted Displays (HMDs) promises to provide users a much better immersive experience. However, HMDs cause hindrance by blocking the facial appearance and expressions of the user. To overcome these issues, we propose a novel attention-enabled encoder-decoder architecture for HMD de-occlusion. We also propose to train our person-specific model using short videos (1-2 minutes) of the user, captured in varying appearances, and demonstrated generalization to unseen poses and appearances of the user. We report superior qualitative and quantitative results over state-of-the-art methods. We also present applications of this approach to hybrid video teleconferencing using existing animation and 3D face reconstruction pipelines.

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