TactStyle: Generating Tactile Textures with Generative AI for Digital Fabrication
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
MFGDiffusion: Mask-Guided Smoke Synthesis for Enhanced Forest Fire Detection
Implementing Adaptations for Vision AutoRegressive Model
CharaConsist: Fine-Grained Consistent Character Generation
MGVQ: Could VQ-VAE Beat VAE? A Generalizable Tokenizer with Multi-group Quantization
NeoBabel: A Multilingual Open Tower for Visual Generation
Estimating Object Physical Properties from RGB-D Vision and Depth Robot Sensors Using Deep Learning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.