MyTimeMachine: Personalized Facial Age Transformation

• URL: http://arxiv.org/abs/2411.14521v1
• Date: Thu, 21 Nov 2024 18:54:13 GMT
• Title: MyTimeMachine: Personalized Facial Age Transformation
• Authors: Luchao Qi, Jiaye Wu, Bang Gong, Annie N. Wang, David W. Jacobs, Roni Sengupta,
• Abstract summary: MyTM combines a global aging prior with a personal photo collection to learn a personalized age transformation. Our approach can also be extended to videos, achieving high-quality, identity-preserving, and temporally consistent aging effects.
• Score: 8.57541218633766
• License:
• Abstract: Facial aging is a complex process, highly dependent on multiple factors like gender, ethnicity, lifestyle, etc., making it extremely challenging to learn a global aging prior to predict aging for any individual accurately. Existing techniques often produce realistic and plausible aging results, but the re-aged images often do not resemble the person's appearance at the target age and thus need personalization. In many practical applications of virtual aging, e.g. VFX in movies and TV shows, access to a personal photo collection of the user depicting aging in a small time interval (20$\sim$40 years) is often available. However, naive attempts to personalize global aging techniques on personal photo collections often fail. Thus, we propose MyTimeMachine (MyTM), which combines a global aging prior with a personal photo collection (using as few as 50 images) to learn a personalized age transformation. We introduce a novel Adapter Network that combines personalized aging features with global aging features and generates a re-aged image with StyleGAN2. We also introduce three loss functions to personalize the Adapter Network with personalized aging loss, extrapolation regularization, and adaptive w-norm regularization. Our approach can also be extended to videos, achieving high-quality, identity-preserving, and temporally consistent aging effects that resemble actual appearances at target ages, demonstrating its superiority over state-of-the-art approaches.

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