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Related papers: Text-Guided Texturing by Synchronized Multi-View D…

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We present Text2Tex, a novel method for generating high-quality textures for 3D meshes from the given text prompts. Our method incorporates inpainting into a pre-trained depth-aware image diffusion model to progressively synthesize high…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Dave Zhenyu Chen , Yawar Siddiqui , Hsin-Ying Lee , Sergey Tulyakov , Matthias Nießner

We present TexFusion (Texture Diffusion), a new method to synthesize textures for given 3D geometries, using large-scale text-guided image diffusion models. In contrast to recent works that leverage 2D text-to-image diffusion models to…

Computer Vision and Pattern Recognition · Computer Science 2023-10-24 Tianshi Cao , Karsten Kreis , Sanja Fidler , Nicholas Sharp , Kangxue Yin

Text-guided video-to-video stylization transforms the visual appearance of a source video to a different appearance guided on textual prompts. Existing text-guided image diffusion models can be extended for stylized video synthesis.…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Minshan Xie , Hanyuan Liu , Chengze Li , Tien-Tsin Wong

Given a 3D mesh, we aim to synthesize 3D textures that correspond to arbitrary textual descriptions. Current methods for generating and assembling textures from sampled views often result in prominent seams or excessive smoothing. To tackle…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Dong Huo , Zixin Guo , Xinxin Zuo , Zhihao Shi , Juwei Lu , Peng Dai , Songcen Xu , Li Cheng , Yee-Hong Yang

Large-scale text-guided image diffusion models have shown astonishing results in text-to-image (T2I) generation. However, applying these models to synthesize textures for 3D geometries remains challenging due to the domain gap between 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Jiawei Lu , Yingpeng Zhang , Zengjun Zhao , He Wang , Kun Zhou , Tianjia Shao

We introduce MD-ProjTex, a method for fast and consistent text-guided texture generation for 3D shapes using pretrained text-to-image diffusion models. At the core of our approach is a multi-view consistency mechanism in UV space, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Ahmet Burak Yildirim , Mustafa Utku Aydogdu , Duygu Ceylan , Aysegul Dundar

The recent success of pre-trained diffusion models unlocks the possibility of the automatic generation of textures for arbitrary 3D meshes in the wild. However, these models are trained in the screen space, while converting them to a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Hongkun Zhang , Zherong Pan , Congyi Zhang , Lifeng Zhu , Xifeng Gao

Given a 3D mesh with a UV parameterization, we introduce a novel approach to generating textures from text prompts. While prior work uses optimization from Text-to-Image Diffusion models to generate textures and geometry, this is slow and…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Julian Knodt , Xifeng Gao

Text-to-texture generation has recently attracted increasing attention, but existing methods often suffer from the problems of view inconsistencies, apparent seams, and misalignment between textures and the underlying mesh. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Jangyeong Kim , Donggoo Kang , Junyoung Choi , Jeonga Wi , Junho Gwon , Jiun Bae , Dumim Yoon , Junghyun Han

3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Lukas Höllein , Aljaž Božič , Norman Müller , David Novotny , Hung-Yu Tseng , Christian Richardt , Michael Zollhöfer , Matthias Nießner

Text-based 2D diffusion models have demonstrated impressive capabilities in image generation and editing. Meanwhile, the 2D diffusion models also exhibit substantial potentials for 3D editing tasks. However, how to achieve consistent edits…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Ruihuang Li , Liyi Chen , Zhengqiang Zhang , Varun Jampani , Vishal M. Patel , Lei Zhang

A fundamental problem in the texturing of 3D meshes using pre-trained text-to-image models is to ensure multi-view consistency. State-of-the-art approaches typically use diffusion models to aggregate multi-view inputs, where common issues…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Zhengyi Zhao , Chen Song , Xiaodong Gu , Yuan Dong , Qi Zuo , Weihao Yuan , Liefeng Bo , Zilong Dong , Qixing Huang

This paper addresses the problem of generating textures for 3D mesh assets. Existing approaches often rely on image diffusion models to generate multi-view image observations, which are then transformed onto the mesh surface to produce a…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Xuyang Wang , Ziang Cheng , Zhenyu Li , Jiayu Yang , Haorui Ji , Pan Ji , Mehrtash Harandi , Richard Hartley , Hongdong Li

Text-to-3D generation, which synthesizes 3D assets according to an overall text description, has significantly progressed. However, a challenge arises when the specific appearances need customizing at designated viewpoints but referring…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Junkai Yan , Yipeng Gao , Qize Yang , Xihan Wei , Xuansong Xie , Ancong Wu , Wei-Shi Zheng

We introduce a general framework for generating diverse visual content, including ambiguous images, panorama images, mesh textures, and Gaussian splat textures, by synchronizing multiple diffusion processes. We present exhaustive…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Jaihoon Kim , Juil Koo , Kyeongmin Yeo , Minhyuk Sung

Texturing is a crucial step in the 3D asset production workflow, which enhances the visual appeal and diversity of 3D assets. Despite recent advancements in Text-to-Texture (T2T) generation, existing methods often yield subpar results,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Wei Cheng , Juncheng Mu , Xianfang Zeng , Xin Chen , Anqi Pang , Chi Zhang , Zhibin Wang , Bin Fu , Gang Yu , Ziwei Liu , Liang Pan

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

Text-guided diffusion models have shown superior performance in image/video generation and editing. While few explorations have been performed in 3D scenarios. In this paper, we discuss three fundamental and interesting problems on this…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Gang Li , Heliang Zheng , Chaoyue Wang , Chang Li , Changwen Zheng , Dacheng Tao

Novel-view synthesis through diffusion models has demonstrated remarkable potential for generating diverse and high-quality images. Yet, the independent process of image generation in these prevailing methods leads to challenges in…

Computer Vision and Pattern Recognition · Computer Science 2024-03-01 Xianghui Yang , Yan Zuo , Sameera Ramasinghe , Loris Bazzani , Gil Avraham , Anton van den Hengel

In this paper, we tackle a new task of 3D object synthesis, where a 3D model is composited with another object category to create a novel 3D model. However, most existing text/image/3D-to-3D methods struggle to effectively integrate…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zeren Xiong , Zikun Chen , Zedong Zhang , Xiang Li , Ying Tai , Jian Yang , Jun Li
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