English
Related papers

Related papers: ConTEXTure: Consistent Multiview Images to Texture

200 papers

Creating 3D textured meshes using generative artificial intelligence has garnered significant attention recently. While existing methods support text-based generative texture generation or editing on 3D meshes, they often struggle to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Yudi Zhang , Qi Xu , Lei Zhang

We present UniTEX, a novel two-stage 3D texture generation framework to create high-quality, consistent textures for 3D assets. Existing approaches predominantly rely on UV-based inpainting to refine textures after reprojecting the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Yixun Liang , Kunming Luo , Xiao Chen , Rui Chen , Hongyu Yan , Weiyu Li , Jiarui Liu , Ping Tan

We present TexTailor, a novel method for generating consistent object textures from textual descriptions. Existing text-to-texture synthesis approaches utilize depth-aware diffusion models to progressively generate images and synthesize…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Suin Lee , Dae-Shik Kim

Here we introduce a new model of natural textures based on the feature spaces of convolutional neural networks optimised for object recognition. Samples from the model are of high perceptual quality demonstrating the generative power of…

Computer Vision and Pattern Recognition · Computer Science 2015-11-09 Leon A. Gatys , Alexander S. Ecker , Matthias Bethge

Large image diffusion models enable novel view synthesis with high quality and excellent zero-shot capability. However, such models based on image-to-image translation have no guarantee of view consistency, limiting the performance for…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Haohan Weng , Tianyu Yang , Jianan Wang , Yu Li , Tong Zhang , C. L. Philip Chen , Lei Zhang

Recently, text-to-image generation has exhibited remarkable advancements, with the ability to produce visually impressive results. In contrast, text-to-3D generation has not yet reached a comparable level of quality. Existing methods…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Yukang Cao , Yan-Pei Cao , Kai Han , Ying Shan , Kwan-Yee K. Wong

Zero-shot novel view synthesis (NVS) from a single image is an essential problem in 3D object understanding. While recent approaches that leverage pre-trained generative models can synthesize high-quality novel views from in-the-wild…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Jianglong Ye , Peng Wang , Kejie Li , Yichun Shi , Heng Wang

We present Im2SurfTex, a method that generates textures for input 3D shapes by learning to aggregate multi-view image outputs produced by 2D image diffusion models onto the shapes' texture space. Unlike existing texture generation…

Graphics · Computer Science 2025-12-11 Yiangos Georgiou , Marios Loizou , Melinos Averkiou , Evangelos Kalogerakis

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

DreamFusion established a new paradigm for unsupervised 3D reconstruction from virtual views by combining advances in generative models and differentiable rendering. However, the underlying multi-view rendering, along with supervision from…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Ananta R. Bhattarai , Xingzhe He , Alla Sheffer , Helge Rhodin

3D point cloud generation by the deep neural network from a single image has been attracting more and more researchers' attention. However, recently-proposed methods require the objects be captured with relatively clean backgrounds, fixed…

Computer Vision and Pattern Recognition · Computer Science 2018-09-11 Yan Xia , Yang Zhang , Dingfu Zhou , Xinyu Huang , Cheng Wang , Ruigang Yang

We present Infinite Texture, a method for generating arbitrarily large texture images from a text prompt. Our approach fine-tunes a diffusion model on a single texture, and learns to embed that statistical distribution in the output domain…

Computer Vision and Pattern Recognition · Computer Science 2024-05-15 Yifan Wang , Aleksander Holynski , Brian L. Curless , Steven M. Seitz

We study the problem of shape generation in 3D mesh representation from a few color images with known camera poses. While many previous works learn to hallucinate the shape directly from priors, we resort to further improving the shape…

Computer Vision and Pattern Recognition · Computer Science 2019-08-19 Chao Wen , Yinda Zhang , Zhuwen Li , Yanwei Fu

Texture map production is an important part of 3D modeling and determines the rendering quality. Recently, diffusion-based methods have opened a new way for texture generation. However, restricted control flexibility and limited prompt…

Graphics · Computer Science 2025-06-04 Dongyu Yan , Leyi Wu , Jiantao Lin , Luozhou Wang , Tianshuo Xu , Zhifei Chen , Zhen Yang , Lie Xu , Shunsi Zhang , Yingcong Chen

3D meshes are widely used in computer vision and graphics for their efficiency in animation and minimal memory use, playing a crucial role in movies, games, AR, and VR. However, creating temporally consistent and realistic textures for mesh…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Jingzhi Bao , Xueting Li , Ming-Hsuan Yang

In this work, we introduce \textbf{Wonder3D++}, a novel method for efficiently generating high-fidelity textured meshes from single-view images. Recent methods based on Score Distillation Sampling (SDS) have shown the potential to recover…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Yuxiao Yang , Xiao-Xiao Long , Zhiyang Dou , Cheng Lin , Yuan Liu , Qingsong Yan , Yuexin Ma , Haoqian Wang , Zhiqiang Wu , Wei Yin

Training native 3D texture generative models remains a fundamental yet challenging problem, largely due to the limited availability of large-scale, high-quality 3D texture datasets. This scarcity hinders generalization to real-world…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Ze Yuan , Xin Yu , Yangtian Sun , Yuan-Chen Guo , Yan-Pei Cao , Ding Liang , Xiaojuan Qi

Scene text images have different shapes and are subjected to various distortions, e.g. perspective distortions. To handle these challenges, the state-of-the-art methods rely on a rectification network, which is connected to the text…

Computer Vision and Pattern Recognition · Computer Science 2022-12-06 Yew Lee Tan , Ernest Yu Kai Chew , Adams Wai-Kin Kong , Jung-Jae Kim , Joo Hwee Lim

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

We present a technique for zero-shot generation of a 3D model using only a target text prompt. Without any 3D supervision our method deforms the control shape of a limit subdivided surface along with its texture map and normal map to obtain…

Computer Vision and Pattern Recognition · Computer Science 2022-09-07 Nasir Mohammad Khalid , Tianhao Xie , Eugene Belilovsky , Tiberiu Popa