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Related papers: TactStyle: Generating Tactile Textures with Genera…

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3D generation methods have shown visually compelling results powered by diffusion image priors. However, they often fail to produce realistic geometric details, resulting in overly smooth surfaces or geometric details inaccurately baked in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ruihan Gao , Kangle Deng , Gengshan Yang , Wenzhen Yuan , Jun-Yan Zhu

Recent developments in Generative AI enable creators to stylize 3D models based on text prompts. These methods change the 3D model geometry, which can compromise the model's structural integrity once fabricated. We present MechStyle, a…

Advances in Generative AI tools have allowed designers to manipulate existing 3D models using text or image-based prompts, enabling creators to explore different design goals. Photochromic color-changing systems, on the other hand, allow…

Human-Computer Interaction · Computer Science 2024-04-29 Yunyi Zhu , Faraz Faruqi , Stefanie Mueller

As several industries are moving towards modeling massive 3D virtual worlds, the need for content creation tools that can scale in terms of the quantity, quality, and diversity of 3D content is becoming evident. In our work, we aim to train…

Computer Vision and Pattern Recognition · Computer Science 2022-09-23 Jun Gao , Tianchang Shen , Zian Wang , Wenzheng Chen , Kangxue Yin , Daiqing Li , Or Litany , Zan Gojcic , Sanja Fidler

The entertainment industry relies on 3D visual content to create immersive experiences, but traditional methods for creating textured 3D models can be time-consuming and subjective. Generative networks such as StyleGAN have advanced image…

Computer Vision and Pattern Recognition · Computer Science 2024-02-09 Yi-Ting Pan , Chai-Rong Lee , Shu-Ho Fan , Jheng-Wei Su , Jia-Bin Huang , Yung-Yu Chuang , Hung-Kuo Chu

Generative AI tools are becoming more prevalent in 3D modeling, enabling users to manipulate or create new models with text or images as inputs. This makes it easier for users to rapidly customize and iterate on their 3D designs and explore…

Human-Computer Interaction · Computer Science 2024-04-18 Faraz Faruqi , Yingtao Tian , Vrushank Phadnis , Varun Jampani , Stefanie Mueller

Tactile sensation plays a crucial role in the development of multi-modal large models and embodied intelligence. To collect tactile data with minimal cost as possible, a series of studies have attempted to generate tactile images by…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Jiahang Tu , Hao Fu , Fengyu Yang , Hanbin Zhao , Chao Zhang , Hui Qian

Deep generative models have various content creation applications such as graphic design, e-commerce, and virtual Try-on. However, current works mainly focus on synthesizing realistic visual outputs, often ignoring other sensory modalities,…

Computer Vision and Pattern Recognition · Computer Science 2023-05-05 Ruihan Gao , Wenzhen Yuan , Jun-Yan Zhu

Design inspiration is crucial for establishing the direction of a design as well as evoking feelings and conveying meanings during the conceptual design process. Many practice designers use text-based searches on platforms like Pinterest to…

Human-Computer Interaction · Computer Science 2024-07-18 Ye Wang , Nicole B. Damen , Thomas Gale , Voho Seo , Hooman Shayani

High-fidelity haptic feedback is essential for immersive virtual environments, yet authoring realistic tactile textures remains a significant bottleneck for designers. We introduce HapticMatch, a visual-to-tactile generation framework…

Human-Computer Interaction · Computer Science 2026-01-26 Mingxin Zhang , Yu Yao , Yasutoshi Makino , Hiroyuki Shinoda , Masashi Sugiyama

Topology optimization(TO) is widely used in engineering because of its ability to save material and optimize structural performance. Although prior work has explored 2D human-centered design tool for TO, the results are often limited in…

Human-Computer Interaction · Computer Science 2026-04-24 Shuyue Feng , Cedric Caremel , Yoshihiro Kawahara

Vision-based tactile sensors, through high-resolution optical measurements, can effectively perceive the geometric shape of objects and the force information during the contact process, thus helping robots acquire higher-dimensional tactile…

Robotics · Computer Science 2026-03-06 Xi Lin , Weiliang Xu , Yixian Mao , Jing Wang , Meixuan Lv , Lu Liu , Xihui Luo , Xinming Li

Style-guided texture generation aims to generate a texture that is harmonious with both the style of the reference image and the geometry of the input mesh, given a reference style image and a 3D mesh with its text description. Although…

Computer Vision and Pattern Recognition · Computer Science 2024-11-04 Zhiyu Xie , Yuqing Zhang , Xiangjun Tang , Yiqian Wu , Dehan Chen , Gongsheng Li , Xaogang Jin

This paper investigates a novel task of generating texture images from perceptual descriptions. Previous work on texture generation focused on either synthesis from examples or generation from procedural models. Generating textures from…

Computer Vision and Pattern Recognition · Computer Science 2017-03-30 Yanhai Gan , Huifang Chi , Ying Gao , Jun Liu , Guoqiang Zhong , Junyu Dong

Recently simulation methods have been developed for optical tactile sensors to enable the Sim2Real learning, i.e., firstly training models in simulation before deploying them on the real robot. However, some artefacts in the real objects…

Robotics · Computer Science 2021-12-06 Tudor Jianu , Daniel Fernandes Gomes , Shan Luo

Providing vibrotactile feedback that corresponds to the state of the virtual texture surfaces allows users to sense haptic properties of them. However, hand-tuning such vibrotactile stimuli for every state of the texture takes much time.…

Human-Computer Interaction · Computer Science 2019-02-21 Yusuke Ujitoko , Yuki Ban

Tactile graphics are essential for providing access to visual information for the 43 million people globally living with vision loss. Traditional methods for creating these graphics are labor-intensive and cannot meet growing demand. We…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Adnan Khan , Alireza Choubineh , Mai A. Shaaban , Abbas Akkasi , Majid Komeili

Generative adversarial networks (GANs) are a recent approach to train generative models of data, which have been shown to work particularly well on image data. In the current paper we introduce a new model for texture synthesis based on GAN…

Computer Vision and Pattern Recognition · Computer Science 2017-09-11 Nikolay Jetchev , Urs Bergmann , Roland Vollgraf

We propose a novel multi-texture synthesis model based on generative adversarial networks (GANs) with a user-controllable mechanism. The user control ability allows to explicitly specify the texture which should be generated by the model.…

Computer Vision and Pattern Recognition · Computer Science 2019-04-25 Aibek Alanov , Max Kochurov , Denis Volkhonskiy , Daniil Yashkov , Evgeny Burnaev , Dmitry Vetrov

Blindness and visual impairments affect many people worldwide. For help with navigation, people with visual impairments often rely on tactile maps that utilize raised surfaces and edges to convey information through touch. Although these…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 David G Hobson , Majid Komeili
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