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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

2D diffusion model, which often contains unwanted baked-in shading effects and results in unrealistic rendering effects in the downstream applications. Generating Physically Based Rendering (PBR) materials instead of just RGB textures would…

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

Recently, the surge of efficient and automated 3D AI-generated content (AIGC) methods has increasingly illuminated the path of transforming human imagination into complex 3D structures. However, the automated generation of 3D content is…

Graphics · Computer Science 2024-12-20 Pei Chen , Fudong Wang , Yixuan Tong , Jingdong Chen , Ming Yang , Minghui Yang

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

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

Manual modeling of material parameters and 3D geometry is a time consuming yet essential task in the gaming and film industries. While recent advances in 3D reconstruction have enabled accurate approximations of scene geometry and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Philipp Langsteiner , Jan-Niklas Dihlmann , Hendrik P. A. Lensch

The increasing demand for 3D assets across various industries necessitates efficient and automated methods for 3D content creation. Leveraging 3D Gaussian Splatting, recent large reconstruction models (LRMs) have demonstrated the ability to…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Jingrui Ye , Lingting Zhu , Runze Zhang , Zeyu Hu , Yingda Yin , Lanjiong Li , Lequan Yu , Qingmin Liao

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

3D object generation from a single image involves estimating the full 3D geometry and texture of unseen views from an unposed RGB image captured in the wild. Accurately reconstructing an object's complete 3D structure and texture has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Hritam Basak , Hadi Tabatabaee , Shreekant Gayaka , Ming-Feng Li , Xin Yang , Cheng-Hao Kuo , Arnie Sen , Min Sun , Zhaozheng Yin

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

We present Material Anything, a fully-automated, unified diffusion framework designed to generate physically-based materials for 3D objects. Unlike existing methods that rely on complex pipelines or case-specific optimizations, Material…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Xin Huang , Tengfei Wang , Ziwei Liu , Qing Wang

We present a method for generating physically-based materials for 3D shapes based on a video diffusion transformer architecture. Our method is conditioned on input geometry and a text description, and jointly models multiple material…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Jon Hasselgren , Zheng Zeng , Milos Hasan , Jacob Munkberg

We leverage finetuned video diffusion models, intrinsic decomposition of videos, and physically-based differentiable rendering to generate high quality materials for 3D models given a text prompt or a single image. We condition a video…

Graphics · Computer Science 2025-06-17 Jacob Munkberg , Zian Wang , Ruofan Liang , Tianchang Shen , Jon Hasselgren

3D texture generation is receiving increasing attention, as it enables the creation of realistic and aesthetic texture materials for untextured 3D meshes. However, existing 3D texture generation methods are limited to producing only a few…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Zhiyuan Zhang , Zijian Zhou , Linjun Li , Long Chen , Hao Tang , Yichen Gong

Despite recent advances in text-to-image generation, controlling geometric layout and PBR material properties in synthesized scenes remains challenging. We present a pipeline that first produces a G-buffer (albedo, normals, depth,…

Graphics · Computer Science 2026-02-10 Bowen Xue , Giuseppe Claudio Guarnera , Shuang Zhao , Zahra Montazeri

We present a novel video generation framework that integrates 3-dimensional geometry and dynamic awareness. To achieve this, we augment 2D videos with 3D point trajectories and align them in pixel space. The resulting 3D-aware video…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Yunuo Chen , Junli Cao , Vidit Goel , Sergei Korolev , Chenfanfu Jiang , Jian Ren , Sergey Tulyakov , Anil Kag

3D generation methods have shown visually compelling results powered by diffusion image priors. However, they often fail to produce realistic geometric details, resulting in overly smooth surfaces or geometric details inaccurately baked in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ruihan Gao , Kangle Deng , Gengshan Yang , Wenzhen Yuan , Jun-Yan Zhu

In this paper, we propose a method to extract physically-based rendering (PBR) materials from a single real-world image. We do so in two steps: first, we map regions of the image to material concepts using a diffusion model, which allows…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Ivan Lopes , Fabio Pizzati , Raoul de Charette

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
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