March 27, 2024, 4:45 a.m. | Stella Bounareli, Christos Tzelepis, Vasileios Argyriou, Ioannis Patras, Georgios Tzimiropoulos

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.17217v1 Announce Type: new
Abstract: Video-driven neural face reenactment aims to synthesize realistic facial images that successfully preserve the identity and appearance of a source face, while transferring the target head pose and facial expressions. Existing GAN-based methods suffer from either distortions and visual artifacts or poor reconstruction quality, i.e., the background and several important appearance details, such as hair style/color, glasses and accessories, are not faithfully reconstructed. Recent advances in Diffusion Probabilistic Models (DPMs) enable the generation of high-quality …

abstract arxiv autoencoder cs.ai cs.cv diffusion face gan head identity images quality type video visual

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Principal Applied Scientist

@ Microsoft | Redmond, Washington, United States

Data Analyst / Action Officer

@ OASYS, INC. | OASYS, INC., Pratt Avenue Northwest, Huntsville, AL, United States