Interp3D: Correspondence-aware Interpolation for Generative Textured 3D Morphing
Textured 3D morphing seeks to generate smooth and plausible transitions between two 3D assets, preserving both structural coherence and fine-grained appearance. This ability is crucial not only for advancing 3D generation research but also for practical applications in animation, editing, and digital content creation. Existing approaches either operate directly on geometry, limiting them to shape-only morphing while neglecting textures, or extend 2D interpolation strategies into 3D, which often causes semantic ambiguity, structural misalignment, and texture blurring. These challenges underscore the necessity to jointly preserve geometric consistency, texture alignment, and robustness throughout the transition process. To address this, we propose Interp3D, a novel training-free framework for textured 3D morphing. It harnesses generative priors and adopts a progressive alignment principle to ensure both geometric fidelity and texture coherence. Starting from semantically aligned interpolation in condition space, Interp3D enforces structural consistency via SLAT (Structured Latent)-guided structure interpolation, and finally transfers appearance details through fine-grained texture fusion. For comprehensive evaluations, we construct a dedicated dataset, Interp3DData, with graded difficulty levels and assess generation results from fidelity, transition smoothness, and plausibility. Both quantitative metrics and human studies demonstrate the significant advantages of our proposed approach over previous methods. Source code is available at https://github.com/xiaolul2/Interp3D.
69718603c1c7409747bf9530
Xiaolu Liu
claimed_verified
2026-01-22T08:45:29.814Z
66863974b9a71fa518a5eea1
/avatars/9012bc92197242fec9801deff65e1e0f.svg
Xiaolu Liu
xiaolul2
user
xiaolul2
69718603c1c7409747bf9531
Yicong Li
69718603c1c7409747bf9532
Qiyuan He
69718603c1c7409747bf9533
Jiayin Zhu
69718603c1c7409747bf9534
Wei Ji
69718603c1c7409747bf9535
Angela Yao
69718603c1c7409747bf9536
Jianke Zhu
Interp3D: Correspondence-aware Interpolation for Generative Textured 3D Morphing
Textured 3D morphing seeks to generate smooth and plausible transitions between two 3D assets, preserving both structural coherence and fine-grained appearance. This ability is crucial not only for advancing 3D generation research but also for practical applications in animation, editing, and digital content creation. Existing approaches either operate directly on geometry, limiting them to shape-only morphing while neglecting textures, or extend 2D interpolation strategies into 3D, which often causes semantic ambiguity, structural misalignment, and texture blurring. These challenges underscore the necessity to jointly preserve geometric consistency, texture alignment, and robustness throughout the transition process. To address this, we propose Interp3D, a novel training-free framework for textured 3D morphing. It harnesses generative priors and adopts a progressive alignment principle to ensure both geometric fidelity and texture coherence. Starting from semantically aligned interpolation in condition space, Interp3D enforces structural consistency via SLAT (Structured Latent)-guided structure interpolation, and finally transfers appearance details through fine-grained texture fusion. For comprehensive evaluations, we construct a dedicated dataset, Interp3DData, with graded difficulty levels and assess generation results from fidelity, transition smoothness, and plausibility. Both quantitative metrics and human studies demonstrate the significant advantages of our proposed approach over previous methods. Source code is available at https://github.com/xiaolul2/Interp3D.
Interp3D is a training-free framework for textured 3D morphing that preserves geometric consistency and texture alignment through generative priors and progressive alignment principles.
textured 3D morphing generative priors progressive alignment SLAT structured latent texture fusion semantically aligned interpolation structural consistency appearance transfer