Single Source One Shot Reenactment using Weighted Motion from Paired Feature Points

Soumya Tripathy, Juho Kannala, Esa Rahtu

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Image reenactment is a task where the target object in the source image imitates the motion represented in the driving image. One of the most common reenactment tasks is face image animation. The major challenge in the current face reenactment approaches is to distinguish between facial motion and identity. For this reason, the previous models struggle to produce high-quality animations if the driving and source identities are different (cross-person reenactment). We propose a new (face) reenactment model that learns shape-independent motion features in a self-supervised setup. The motion is represented using a set of paired feature points extracted from the source and driving images simultaneously. The model is generalised to multiple reenactment tasks including faces and non-face objects using only a single source image. The extensive experiments show that the model faithfully transfers the driving motion to the source while retaining the source identity intact.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022
PublisherIEEE
Pages2121-2130
Number of pages10
ISBN (Electronic)9781665409155
DOIs
Publication statusPublished - 2022
Publication typeA4 Article in conference proceedings
EventIEEE/CVF Winter Conference on Applications of Computer Vision - Waikoloa, United States
Duration: 4 Jan 20228 Jan 2022

Publication series

NameProceedings - 2022 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022
ISSN (Electronic)2642-9381

Workshop

WorkshopIEEE/CVF Winter Conference on Applications of Computer Vision
Country/TerritoryUnited States
CityWaikoloa
Period4/01/228/01/22

Keywords

  • Autoencoders
  • Deep Learning
  • GANs Deep Learning
  • Neural Generative Models

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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