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Physically-based rendering (PBR) has become a cornerstone in modern computer graphics, enabling realistic material representation and lighting interactions in 3D scenes. In this paper, we present MaterialMVP, a novel end-to-end model for…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Zebin He , Mingxin Yang , Shuhui Yang , Yixuan Tang , Tao Wang , Kaihao Zhang , Guanying Chen , Yuhong Liu , Jie Jiang , Chunchao Guo , Wenhan Luo

We present PBR-SR, a novel method for physically based rendering (PBR) texture super resolution (SR). It outputs high-resolution, high-quality PBR textures from low-resolution (LR) PBR input in a zero-shot manner. PBR-SR leverages an…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Yujin Chen , Yinyu Nie , Benjamin Ummenhofer , Reiner Birkl , Michael Paulitsch , Matthias Nießner

Physically-based rendering (PBR) provides a principled standard for realistic material-lighting interactions in computer graphics. Despite recent advances in generating PBR textures, existing methods fail to address two fundamental…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Jingzhi Bao , Hongze Chen , Lingting Zhu , Chenyu Liu , Runze Zhang , Keyang Luo , Zeyu Hu , Weikai Chen , Yingda Yin , Xin Wang , Zehong Lin , Jun Zhang , Xiaoguang Han

Existing 2D methods utilize UNet-based diffusion models to generate multi-view physically-based rendering (PBR) maps but struggle with multi-view inconsistency, while some 3D methods directly generate UV maps, encountering generalization…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Shenhao Zhu , Lingteng Qiu , Xiaodong Gu , Zhengyi Zhao , Chao Xu , Yuxiao He , Zhe Li , Xiaoguang Han , Yao Yao , Xun Cao , Siyu Zhu , Weihao Yuan , Zilong Dong , Hao Zhu

Physically Based Rendering (PBR) materials play a crucial role in modern graphics, enabling photorealistic rendering across diverse environment maps. Developing an effective and efficient algorithm that is capable of automatically…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Bojun Xiong , Jialun Liu , Jiakui Hu , Chenming Wu , Jinbo Wu , Xing Liu , Chen Zhao , Errui Ding , Zhouhui Lian

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

Generating high-quality physically based rendering (PBR) materials is important to achieve realistic rendering in the downstream tasks, yet it remains challenging due to the intertwined effects of materials and lighting. While existing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Xiaokang Wei , Bowen Zhang , Xianghui Yang , Yuxuan Wang , Chunchao Guo , Xi Zhao , Yan Luximon

Automatic 3D content creation has gained increasing attention recently, due to its potential in various applications such as video games, film industry, and AR/VR. Recent advancements in diffusion models and multimodal models have notably…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Yitong Wang , Xudong Xu , Li Ma , Haoran Wang , Bo Dai

Generating high-quality, photorealistic textures for 3D human avatars remains a fundamental yet challenging task in computer vision and multimedia field. However, real paired front and back images of human subjects are rarely available with…

Graphics · Computer Science 2026-04-10 Mingxiao Tu , Shuchang Ye , Hoijoon Jung , Jinman Kim

Vastextures is a vast repository of 500,000 textures and PBR materials extracted from real-world images using an unsupervised process. The extracted materials and textures are extremely diverse and cover a vast range of real-world patterns,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Sagi Eppel

In this paper, we introduce MeshGen, an advanced image-to-3D pipeline that generates high-quality 3D meshes with detailed geometry and physically based rendering (PBR) textures. Addressing the challenges faced by existing 3D native…

Graphics · Computer Science 2025-05-09 Zilong Chen , Yikai Wang , Wenqiang Sun , Feng Wang , Yiwen Chen , Huaping Liu

Existing industrial 3D garment meshes already cover most real-world clothing geometries, yet their texture diversity remains limited. To acquire more realistic textures, generative methods are often used to extract Physically-based…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Hui Shan , Ming Li , Haitao Yang , Kai Zheng , Sizhe Zheng , Yanwei Fu , Xiangru Huang

In this paper, we present TexPro, a novel method for high-fidelity material generation for input 3D meshes given text prompts. Unlike existing text-conditioned texture generation methods that typically generate RGB textures with baked…

Graphics · Computer Science 2025-05-20 Ziqiang Dang , Wenqi Dong , Zesong Yang , Bangbang Yang , Liang Li , Yuewen Ma , Zhaopeng Cui

We present Make-A-Texture, a new framework that efficiently synthesizes high-resolution texture maps from textual prompts for given 3D geometries. Our approach progressively generates textures that are consistent across multiple viewpoints…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Xiaoyu Xiang , Liat Sless Gorelik , Yuchen Fan , Omri Armstrong , Forrest Iandola , Yilei Li , Ita Lifshitz , Rakesh Ranjan

Recently, significant advances have been made in 3D object generation. Building upon the generated geometry, current pipelines typically employ image diffusion models to generate multi-view RGB images, followed by UV texture reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Mingqi Shao , Feng Xiong , Zhaoxu Sun , Mu Xu

Prior material creation methods had limitations in producing diverse results mainly because reconstruction-based methods relied on real-world measurements and generation-based methods were trained on relatively small material datasets. To…

Computer Vision and Pattern Recognition · Computer Science 2024-07-02 Linxuan Xin , Zheng Zhang , Jinfu Wei , Wei Gao , Duan Gao

In this paper, we present TEXTure, a novel method for text-guided generation, editing, and transfer of textures for 3D shapes. Leveraging a pretrained depth-to-image diffusion model, TEXTure applies an iterative scheme that paints a 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-02-06 Elad Richardson , Gal Metzer , Yuval Alaluf , Raja Giryes , Daniel Cohen-Or

This report presents a comprehensive framework for generating high-quality 3D shapes and textures from diverse input prompts, including single images, multi-view images, and text descriptions. The framework consists of 3D shape generation…

While physically-based rendering (PBR) simulates light transport that guarantees physical realism, achieving true photorealistic rendering (PRR) demands prohibitive time and labor, and still struggles to capture the intractable richness of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Jiayuan Lu , Rengan Xie , Xuancheng Jin , Zhizhen Wu , Qi Ye , Tian Xie , Hujun Bao , Rui Wang. Yuchi Huo

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
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