Wukong's 72 Transformations: High-fidelity Textured 3D Morphing via Flow Models

• URL: http://arxiv.org/abs/2511.22425v1
• Date: Thu, 27 Nov 2025 13:03:57 GMT
• Title: Wukong's 72 Transformations: High-fidelity Textured 3D Morphing via Flow Models
• Authors: Minghao Yin, Yukang Cao, Kai Han,
• Abstract summary: WUKONG is a training-free framework for high-fidelity textured 3D morphing.<n>We exploit the inherent continuity of flow-based generative processes.<n>We propose a similarity-guided semantic consistency mechanism.
• Score: 33.80986417412425
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present WUKONG, a novel training-free framework for high-fidelity textured 3D morphing that takes a pair of source and target prompts (image or text) as input. Unlike conventional methods -- which rely on manual correspondence matching and deformation trajectory estimation (limiting generalization and requiring costly preprocessing) -- WUKONG leverages the generative prior of flow-based transformers to produce high-fidelity 3D transitions with rich texture details. To ensure smooth shape transitions, we exploit the inherent continuity of flow-based generative processes and formulate morphing as an optimal transport barycenter problem. We further introduce a sequential initialization strategy to prevent abrupt geometric distortions and preserve identity coherence. For faithful texture preservation, we propose a similarity-guided semantic consistency mechanism that selectively retains high-frequency details and enables precise control over blending dynamics. This avoids common artifacts like oversmoothing while maintaining semantic fidelity. Extensive quantitative and qualitative evaluations demonstrate that WUKONG significantly outperforms state-of-the-art methods, achieving superior results across diverse geometry and texture variations.

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