TactStyle: Generating Tactile Textures with Generative AI for Digital Fabrication
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Abstract (arXiv)
Recent work in Generative AI enables the stylization of 3D models based on image prompts. However, these methods do not incorporate tactile information, leading to designs that lack the expected tactile properties. We present TactStyle, a system that allows creators to stylize 3D models with images while incorporating the expected tactile properties. TactStyle accomplishes this using a modified image-generation model fine-tuned to generate heightfields for given surface textures. By optimizing 3D model surfaces to embody a generated texture, TactStyle creates models that match the desired style and replicate the tactile experience. We utilize a large-scale dataset of textures to train our texture generation model. In a psychophysical experiment, we evaluate the tactile qualities of a set of 3D-printed original textures and TactStyle's generated textures. Our results show that TactStyle successfully generates a wide range of tactile features from a single image input, enabling a novel approach to haptic design.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 12 of its 61 references that are in the map. First posted on arXiv 3 Mar 2025.
Builds on
12 of 61 references.
References · 12
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
- 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,903
- 2022GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Imagescited by 446
- 2024InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Modelscited by 421
- 2021Text2Mesh: Text-Driven Neural Stylization for Meshescited by 332
- 2024TextureDreamer: Image-guided Texture Synthesis through Geometry-aware Diffusioncited by 51
- 2023X-Mesh: Towards Fast and Accurate Text-driven 3D Stylization via Dynamic Textual Guidancecited by 37
- 2023Style2Fab: Functionality-Aware Segmentation for Fabricating Personalized 3D Models with Generative AIcited by 11
- 2024Shaping Realities: Enhancing 3D Generative AI with Fabrication Constraintscited by 6
- 2021SliceHub: Augmenting Shared 3D Model Repositories with Slicing Results for 3D Printingcited by 5
- 2022Shape-Haptics: Planar & Passive Force Feedback Mechanisms for Physical Interfacescited by 1
Built on by
Citing papers per year: 2025: 1; 2026: 3.
4 papers.
- 2025MechStyle: Augmenting Generative AI with Mechanical Simulation to Create Stylized and Structurally Viable 3D Modelscited by 1
- 2026Why Modeling Human Haptic Material Perception with AI Is Difficultcited by 0
- 2026Compos3D: Interactive Part-Based Composition for Creative Control in Generative 3D Modelscited by 0
- 2026InstructMesh: Selective Refinement of Generative 3D Models for Fabricationcited by 0
- 2026InstructMesh: Selective Refinement of Generative 3D Models for Fabrication28 Aug 2026
- 2026Compos3D: Interactive Part-Based Composition for Creative Control in Generative 3D Models13 Jul 2026
- 2026Why Modeling Human Haptic Material Perception with AI Is Difficult15 May 2026
- 2025MechStyle: Augmenting Generative AI with Mechanical Simulation to Create Stylized and Structurally Viable 3D Models24 Sep 2025