ReAge3D: Re-Aging 3D Faces with View Consistency

• URL: http://arxiv.org/abs/2606.18156v1
• Date: Tue, 16 Jun 2026 16:56:00 GMT
• Title: ReAge3D: Re-Aging 3D Faces with View Consistency
• Abstract summary: We present a novel framework for realistic and controllable 3D face re-aging.<n>Our method outperforms existing 3D editing techniques both visually and quantitatively.
• Score: 13.665108404343245
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: We present a novel framework for realistic and controllable 3D face re-aging which produces highly detailed, identity-preserving results. Existing 3D editing methods, while effective for coarse semantic changes, are not well suited for re-aging, as even small inconsistencies across re-aged 2D views can lead to over-smoothing of subtle but perceptually important age-related details. To address this challenge, we first introduce a 2D diffusion-based re-aging model, DiffReaging, trained on synthetically generated image pairs. We further propose a center-out editing propagation strategy that leverages this re-aging model to reconstruct multi-view-consistent re-aged images. Specifically, starting from a re-aged frontal pivot view, we reconstruct the remaining views through warping and our proposed Masked-DiffReaging process. By injecting existing content at every step of the diffusion process, Masked-DiffReaging ensures that the reconstructed regions remain coherent with existing pixels. The resulting consistent set of re-aged views supervises the optimization of the re-aged 3D representation. Our method outperforms existing 3D editing techniques both visually and quantitatively, enabling smooth, fine-grained control over age transformations in 3D face models.

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