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Related papers: Make-A-Texture: Fast Shape-Aware Texture Generatio…

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We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D meshes generation from a single unposed image in the wild using both2D and 3D priors. In the first stage, we optimize a neural radiance field to produce…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Guocheng Qian , Jinjie Mai , Abdullah Hamdi , Jian Ren , Aliaksandr Siarohin , Bing Li , Hsin-Ying Lee , Ivan Skorokhodov , Peter Wonka , Sergey Tulyakov , Bernard Ghanem

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

The modern computer graphics pipeline can synthesize images at remarkable visual quality; however, it requires well-defined, high-quality 3D content as input. In this work, we explore the use of imperfect 3D content, for instance, obtained…

Computer Vision and Pattern Recognition · Computer Science 2019-04-30 Justus Thies , Michael Zollhöfer , Matthias Nießner

Manually creating textures for 3D meshes is time-consuming, even for expert visual content creators. We propose a fast approach for automatically texturing an input 3D mesh based on a user-provided text prompt. Importantly, our approach…

Despite the availability of large-scale 3D datasets and advancements in 3D generative models, the complexity and uneven quality of 3D geometry and texture data continue to hinder the performance of 3D generation techniques. In most existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Xin Yang , Jiantao Lin , Yingjie Xu , Haodong Li , Yingcong Chen

Texture reconstruction techniques generally suffer from the errors in keyframe poses. We present a non-iterative method for seamless texture reconstruction of a given 3D scene. Our method finds the best texture alignment in a single shot…

Computer Vision and Pattern Recognition · Computer Science 2020-11-03 Mohammad Rouhani , Matthieu Fradet , Caroline Baillard

This paper presents an extension to the KinectFusion algorithm which allows creating simplified 3D models with high quality RGB textures. This is achieved through (i) creating model textures using images from an HD RGB camera that is…

Graphics · Computer Science 2016-02-23 Song Liu , Wanqing Li , Philip Ogunbona , Yang-Wai Chow

We study the problem of 3D-aware full-body human generation, aiming at creating animatable human avatars with high-quality textures and geometries. Generally, two challenges remain in this field: i) existing methods struggle to generate…

Computer Vision and Pattern Recognition · Computer Science 2023-10-05 Xuanmeng Zhang , Jianfeng Zhang , Rohan Chacko , Hongyi Xu , Guoxian Song , Yi Yang , Jiashi Feng

We propose a Transformer-based framework for 3D human texture estimation from a single image. The proposed Transformer is able to effectively exploit the global information of the input image, overcoming the limitations of existing methods…

Computer Vision and Pattern Recognition · Computer Science 2021-09-07 Xiangyu Xu , Chen Change Loy

We present a data-driven inference method that can synthesize a photorealistic texture map of a complete 3D face model given a partial 2D view of a person in the wild. After an initial estimation of shape and low-frequency albedo, we…

Computer Vision and Pattern Recognition · Computer Science 2016-12-05 Shunsuke Saito , Lingyu Wei , Liwen Hu , Koki Nagano , Hao Li

We present GenesisTex, a novel method for synthesizing textures for 3D geometries from text descriptions. GenesisTex adapts the pretrained image diffusion model to texture space by texture space sampling. Specifically, we maintain a latent…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Chenjian Gao , Boyan Jiang , Xinghui Li , Yingpeng Zhang , Qian Yu

In this report, we introduce UltraShape 1.0, a scalable 3D diffusion framework for high-fidelity 3D geometry generation. The proposed approach adopts a two-stage generation pipeline: a coarse global structure is first synthesized and then…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Tanghui Jia , Dongyu Yan , Dehao Hao , Yang Li , Kaiyi Zhang , Xianyi He , Lanjiong Li , Yuhan Wang , Jinnan Chen , Lutao Jiang , Qishen Yin , Long Quan , Ying-Cong Chen , Li Yuan

There has been significant progress in generating an animatable 3D human avatar from a single image. However, recovering texture for the 3D human avatar from a single image has been relatively less addressed. Because the generated 3D human…

Computer Vision and Pattern Recognition · Computer Science 2023-05-02 Sihun Cha , Kwanggyoon Seo , Amirsaman Ashtari , Junyong Noh

There is a growing demand for customized and expressive 3D characters with the emergence of AI agents and Metaverse, but creating 3D characters using traditional computer graphics tools is a complex and time-consuming task. To address these…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Jianqiang Ren , Chao He , Lin Liu , Jiahao Chen , Yutong Wang , Yafei Song , Jianfang Li , Tangli Xue , Siqi Hu , Tao Chen , Kunkun Zheng , Jianjing Xiang , Liefeng Bo

An explainable, efficient and lightweight method for texture generation, called TGHop (an acronym of Texture Generation PixelHop), is proposed in this work. Although synthesis of visually pleasant texture can be achieved by deep neural…

Computer Vision and Pattern Recognition · Computer Science 2021-07-09 Xuejing Lei , Ganning Zhao , Kaitai Zhang , C. -C. Jay Kuo

We introduce TM-NET, a novel deep generative model for synthesizing textured meshes in a part-aware manner. Once trained, the network can generate novel textured meshes from scratch or predict textures for a given 3D mesh, without image…

Graphics · Computer Science 2021-06-10 Lin Gao , Tong Wu , Yu-Jie Yuan , Ming-Xian Lin , Yu-Kun Lai , Hao Zhang

Recent GAN-based (Generative adversarial networks) inpainting methods show remarkable improvements and generate plausible images using multi-stage networks or Contextual Attention Modules (CAM). However, these techniques increase the model…

Computer Vision and Pattern Recognition · Computer Science 2021-02-16 Mohamed Abbas Hedjazi , Yakup Genc

We present a super-resolution method capable of creating a high-resolution texture map for a virtual 3D object from a set of lower-resolution images of that object. Our architecture unifies the concepts of (i) multi-view super-resolution…

Computer Vision and Pattern Recognition · Computer Science 2020-01-15 Audrey Richard , Ian Cherabier , Martin R. Oswald , Vagia Tsiminaki , Marc Pollefeys , Konrad Schindler

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

While recent generative models for 2D images achieve impressive visual results, they clearly lack the ability to perform 3D reasoning. This heavily restricts the degree of control over generated objects as well as the possible applications…

Computer Vision and Pattern Recognition · Computer Science 2020-10-26 Dario Pavllo , Graham Spinks , Thomas Hofmann , Marie-Francine Moens , Aurelien Lucchi
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