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Coarse architectural models are often generated at scales ranging from individual buildings to scenes for downstream applications such as Digital Twin City, Metaverse, LODs, etc. Such piece-wise planar models can be abstracted as twins from…

Graphics · Computer Science 2023-09-21 Weidan Xiong , Hongqian Zhang , Botao Peng , Ziyu Hu , Yongli Wu , Jianwei Guo , Hui Huang

Prevailing image representation methods, including explicit representations such as raster images and Gaussian primitives, as well as implicit representations such as latent images, either suffer from representation redundancy that leads to…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Ye Chen , Yupeng Zhu , Xiongzhen Zhang , Zhewen Wan , Yingzhe Li , Wenjun Zhang , Bingbing Ni

Generating high-quality textures for 3D scenes is crucial for applications in interior design, gaming, and augmented/virtual reality (AR/VR). Although recent advancements in 3D generative models have enhanced content creation, significant…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Yunfan Zhang , Zhiwei Xiong , Zhiqi Shen , Guosheng Lin , Hao Wang , Nicolas Vun

While high-quality texture maps are essential for realistic 3D asset rendering, few studies have explored learning directly in the texture space, especially on large-scale datasets. In this work, we depart from the conventional approach of…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Xin Yu , Ze Yuan , Yuan-Chen Guo , Ying-Tian Liu , JianHui Liu , Yangguang Li , Yan-Pei Cao , Ding Liang , Xiaojuan Qi

The advancement of diffusion models has pushed the boundary of text-to-3D object generation. While it is straightforward to composite objects into a scene with reasonable geometry, it is nontrivial to texture such a scene perfectly due to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Qi Wang , Ruijie Lu , Xudong Xu , Jingbo Wang , Michael Yu Wang , Bo Dai , Gang Zeng , Dan Xu

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

Reconstructing transparent objects from a set of multi-view images is a challenging task due to the complicated nature and indeterminate behavior of light propagation. Typical methods are primarily tailored to specific scenarios, such as…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Changpu Li , Shuang Wu , Songlin Tang , Guangming Lu , Jun Yu , Wenjie Pei

Accurate modeling of 3D objects exhibiting transparency, reflections and thin structures is an extremely challenging problem. Inspired by billboards and geometric proxies used in computer graphics, this paper proposes Generative Latent…

Computer Vision and Pattern Recognition · Computer Science 2020-08-12 Ricardo Martin-Brualla , Rohit Pandey , Sofien Bouaziz , Matthew Brown , Dan B Goldman

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

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

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

Precise human mesh recovery (HMR) from multi-view images remains challenging: end-to-end methods produce entangled errors hard to localize, while fitting-based methods rely on sparse keypoints that provide limited surface constraints. We…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Renke Wang , Zhenyu Zhang , Ying Tai , Jun Li , Jian Yang

Learning-based 3D reconstruction methods have shown impressive results. However, most methods require 3D supervision which is often hard to obtain for real-world datasets. Recently, several works have proposed differentiable rendering…

Computer Vision and Pattern Recognition · Computer Science 2020-03-24 Michael Niemeyer , Lars Mescheder , Michael Oechsle , Andreas Geiger

We introduce DiffBMP, a scalable and efficient differentiable rendering engine for a collection of bitmap images. Our work addresses a limitation that traditional differentiable renderers are constrained to vector graphics, given that most…

Graphics · Computer Science 2026-03-25 Seongmin Hong , Junghun James Kim , Daehyeop Kim , Insoo Chung , Se Young Chun

Due to inevitable noises introduced during scanning and quantization, 3D reconstruction via RGB-D sensors suffers from errors both in geometry and texture, leading to artifacts such as camera drifting, mesh distortion, texture ghosting, and…

Computer Vision and Pattern Recognition · Computer Science 2022-09-13 Jingbo Zhang , Ziyu Wan , Jing Liao

Recent data-driven image colorization methods have enabled automatic or reference-based colorization, while still suffering from unsatisfactory and inaccurate object-level color control. To address these issues, we propose a new method…

Computer Vision and Pattern Recognition · Computer Science 2023-08-04 Jianxin Lin , Peng Xiao , Yijun Wang , Rongju Zhang , Xiangxiang Zeng

Prevailing 3D texture generation methods, which often rely on multi-view fusion, are frequently hindered by inter-view inconsistencies and incomplete coverage of complex surfaces, limiting the fidelity and completeness of the generated…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Yifei Zeng , Yajie Bao , Jiachen Qian , Shuang Wu , Youtian Lin , Hao Zhu , Buyu Li , Feihu Zhang , Xun Cao , Yao Yao

Real-time rendering of dynamic line sets is relevant in many visualization tasks, including unsteady flow visualization and interactive white matter reconstruction from Magnetic Resonance Imaging. High-quality global illumination and…

Graphics · Computer Science 2026-02-13 Bram Kraaijeveld , Andrei C. Jalba , Anna Vilanova , Maxime Chamberland

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

Graph-based procedural materials are ubiquitous in content production industries. Procedural models allow the creation of photorealistic materials with parametric control for flexible editing of appearance. However, designing a specific…

Graphics · Computer Science 2022-07-19 Yiwei Hu , Paul Guerrero , Miloš Hašan , Holly Rushmeier , Valentin Deschaintre
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