JanusMesh: Fast and Zero-Shot 3D Visual Illusion Generation via Cross-Space Denoising

Creating 3D visual illusions, a single 3D mesh that revealsentirely different semantics from various viewing angles, is a fascinat-ing but tough challenge. Existing optimization-based methods are slowand can produce oversaturated colors. In contrast, naive stitching ap-proaches fail to produce geometrically coherent objects. This results invisible unnatural seams and semantic leaks. In this paper, we presenta fast and training-free framework for generating text-driven 3D visualillusions. Our approach decouples the generation into two stages. First,we propose a cross-space dual-branch denoising process. This processdynamically decodes 3D latents into voxel space for CLIP-guided orien-tation alignment and Signed Distance Field (SDF) blending, which en-sures seamless geometric fusion. Second, we introduce a view-conditionedtexture synthesis module that projects and aggregates view-specific 2Ddiffusion priors onto the fused geometry. Extensive experiments demon-strate that our method generates highly realistic, dual-semantic 3D illu-sions in just 3–5 minutes. It significantly outperforms existing methodsin geometric integrity, semantic recognizability, and efficiency. Projectpage: https://siang1105.github.io/JanusMesh.github.io/Target Junction view Target Junction view Target Junction viewview view view“A parrot”𝜃" 𝜃" 𝜃"Target Target Targetview view view𝜃! 𝜃! 𝜃!“A boat”❌ Severe over-saturation ❌ Visible backside leakage ✅ Dual-semantic coherency❌ Slow optimization (~40 min) ❌ Unnatural geometric seams ✅ Fast & Training-free (~3-5 min)(a) SDS-Based Method (b) Direct Concatenation (c) OursFig. 2: Comparison of 3D visual illusion generation methods. (a) SDS-BasedMethods suffer from severe over-saturation and slow optimization. (b) Direct Con-catenation exposes unnatural geometric seams and semantic leakage at target views(red arrows). (c) Our method creates a seamless, dual-semantic coherent 3D mesh.Unlike previous approaches, our method does not require training. It generates high-quality 3D visual illusions in just 3–5 minutes while completely preventing geometricinterference between the two semantics.