The Aging Multiverse: Generating Condition-Aware Facial Aging Tree via Training-Free Diffusion

• URL: http://arxiv.org/abs/2506.21008v3
• Date: Wed, 06 Aug 2025 16:50:46 GMT
• Title: The Aging Multiverse: Generating Condition-Aware Facial Aging Tree via Training-Free Diffusion
• Authors: Bang Gong, Luchao Qi, Jiaye Wu, Zhicheng Fu, Chunbo Song, David W. Jacobs, John Nicholson, Roni Sengupta,
• Abstract summary: We introduce the Aging Multiverse, a framework for generating multiple plausible facial aging trajectories from a single image.<n>We propose a training-free diffusion-based method that balances identity preservation, age accuracy, and condition control.<n>Experiments and user studies demonstrate state-of-the-art performance across identity preservation, aging realism, and conditional alignment.
• Score: 7.536205940569963
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We introduce the Aging Multiverse, a framework for generating multiple plausible facial aging trajectories from a single image, each conditioned on external factors such as environment, health, and lifestyle. Unlike prior methods that model aging as a single deterministic path, our approach creates an aging tree that visualizes diverse futures. To enable this, we propose a training-free diffusion-based method that balances identity preservation, age accuracy, and condition control. Our key contributions include attention mixing to modulate editing strength and a Simulated Aging Regularization strategy to stabilize edits. Extensive experiments and user studies demonstrate state-of-the-art performance across identity preservation, aging realism, and conditional alignment, outperforming existing editing and age-progression models, which often fail to account for one or more of the editing criteria. By transforming aging into a multi-dimensional, controllable, and interpretable process, our approach opens up new creative and practical avenues in digital storytelling, health education, and personalized visualization.

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