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Related papers: ePBR: Extended PBR Materials in Image Synthesis

200 papers

Graphics pipelines require physically-based rendering (PBR) materials, yet current 3D content generation approaches are built on RGB models. We propose to model the PBR image distribution directly, avoiding photometric inaccuracies in RGB…

Computer Vision and Pattern Recognition · Computer Science 2024-08-26 Shimon Vainer , Mark Boss , Mathias Parger , Konstantin Kutsy , Dante De Nigris , Ciara Rowles , Nicolas Perony , Simon Donné

Synthesizing photo-realistic images and videos is at the heart of computer graphics and has been the focus of decades of research. Traditionally, synthetic images of a scene are generated using rendering algorithms such as rasterization or…

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

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

Understanding and modeling lighting effects are fundamental tasks in computer vision and graphics. Classic physically-based rendering (PBR) accurately simulates the light transport, but relies on precise scene representations--explicit 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Ruofan Liang , Zan Gojcic , Huan Ling , Jacob Munkberg , Jon Hasselgren , Zhi-Hao Lin , Jun Gao , Alexander Keller , Nandita Vijaykumar , Sanja Fidler , Zian Wang

Recent advancements in large generative models, particularly diffusion-based methods, have significantly enhanced the capabilities of image editing. However, achieving precise control over image composition tasks remains a challenge.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Jinrui Yang , Qing Liu , Yijun Li , Soo Ye Kim , Daniil Pakhomov , Mengwei Ren , Jianming Zhang , Zhe Lin , Cihang Xie , Yuyin Zhou

Mobile robots operating indoors must be prepared to navigate challenging scenes that contain transparent surfaces. This paper proposes a novel method for the fusion of acoustic and visual sensing modalities through implicit neural…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Advaith V. Sethuraman , Onur Bagoren , Harikrishnan Seetharaman , Dalton Richardson , Joseph Taylor , Katherine A. Skinner

Mathematically representing the shape of an object is a key ingredient for solving inverse rendering problems. Explicit representations like meshes are efficient to render in a differentiable fashion but have difficulties handling topology…

Graphics · Computer Science 2022-07-12 Guangyan Cai , Kai Yan , Zhao Dong , Ioannis Gkioulekas , Shuang Zhao

Automatic document content processing is affected by artifacts caused by the shape of the paper, non-uniform and diverse color of lighting conditions. Fully-supervised methods on real data are impossible due to the large amount of data…

Computer Vision and Pattern Recognition · Computer Science 2020-12-01 Sagnik Das , Hassan Ahmed Sial , Ke Ma , Ramon Baldrich , Maria Vanrell , Dimitris Samaras

The lack of labeled datasets in 3D vision for surgical scenes inhibits the development of robust 3D reconstruction algorithms in the medical domain. Despite the popularity of Neural Radiance Fields and 3D Gaussian Splatting in the general…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 John J. Han , Jie Ying Wu

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…

Synthetic image datasets offer unmatched advantages for designing and evaluating deep neural networks: they make it possible to (i) render as many data samples as needed, (ii) precisely control each scene and yield granular ground truth…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Florian Bordes , Shashank Shekhar , Mark Ibrahim , Diane Bouchacourt , Pascal Vincent , Ari S. Morcos

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

Achieving physically consistent image editing remains a significant challenge in computer vision. Existing image editing methods typically rely on neural networks, which struggle to accurately handle shadows and refractions. Conversely,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Lezhong Wang , Duc Minh Tran , Ruiqi Cui , Thomson TG , Anders Bjorholm Dahl , Siavash Arjomand Bigdeli , Jeppe Revall Frisvad , Manmohan Chandraker

Three-dimensional reconstruction of events recorded on images has been a common challenge between computer vision and computer graphics for a long time. Estimating the real position of objects and surfaces using vision as an input is no…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Rafael Kuffner dos Anjos , João Madeiras Pereira , José Antonio Gaspar

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

Implicit Neural Representations (INRs) are a novel paradigm for signal representation that have attracted considerable interest for image compression. INRs offer unprecedented advantages in signal resolution and memory efficiency, enabling…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Marcos V. Conde , Andy Bigos , Radu Timofte

A unique challenge in creating high-quality animatable and relightable 3D avatars of people is modeling human eyes. The challenge of synthesizing eyes is multifold as it requires 1) appropriate representations for the various components of…

Computer Vision and Pattern Recognition · Computer Science 2022-07-13 Gengyan Li , Abhimitra Meka , Franziska Müller , Marcel C. Bühler , Otmar Hilliges , Thabo Beeler

In an era where numerous studies claim to achieve almost photorealism with real-time automated environment capture, there is a need for assessments and reproducibility in this domain. This paper presents a transparent and reproducible user…

Human-Computer Interaction · Computer Science 2024-07-03 Sven Kluge , Oliver Staadt

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