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Physically-based rendering (PBR) is key for immersive rendering effects used widely in the industry to showcase detailed realistic scenes from computer graphics assets. A well-known caveat is that producing the same is computationally heavy…

Computer Vision and Pattern Recognition · Computer Science 2023-04-13 Jing Yang , Hanyuan Xiao , Wenbin Teng , Yunxuan Cai , Yajie Zhao

Recent works in inverse rendering have shown promise in using multi-view images of an object to recover shape, albedo, and materials. However, the recovered components often fail to render accurately under new lighting conditions due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yehonathan Litman , Or Patashnik , Kangle Deng , Aviral Agrawal , Rushikesh Zawar , Fernando De la Torre , Shubham Tulsiani

Current methods for 3D generation still fall short in physically based rendering (PBR) texturing, primarily due to limited data and challenges in modeling multi-channel materials. In this work, we propose MuMA, a method for 3D PBR texturing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Lingting Zhu , Jingrui Ye , Runze Zhang , Zeyu Hu , Yingda Yin , Lanjiong Li , Jinnan Chen , Shengju Qian , Xin Wang , Qingmin Liao , Lequan Yu

Real-time rendering and animation of humans is a core function in games, movies, and telepresence applications. Existing methods have a number of drawbacks we aim to address with our work. Triangle meshes have difficulty modeling thin…

We introduce IntrinsiX, a novel method that generates high-quality intrinsic images from text description. In contrast to existing text-to-image models whose outputs contain baked-in scene lighting, our approach predicts physically-based…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Peter Kocsis , Lukas Höllein , Matthias Nießner

We present a tool for enhancing the detail of physically based materials using an off-the-shelf diffusion model and inverse rendering. Our goal is to enhance the visual fidelity of materials with detail that is often tedious to author, by…

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

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 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

We present DualMat, a novel dual-path diffusion framework for estimating Physically Based Rendering (PBR) materials from single images under complex lighting conditions. Our approach operates in two distinct latent spaces: an…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Yifeng Huang , Zhang Chen , Yi Xu , Minh Hoai , Zhong Li

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

We present Stable Video Materials 3D (SViM3D), a framework to predict multi-view consistent physically based rendering (PBR) materials, given a single image. Recently, video diffusion models have been successfully used to reconstruct 3D…

Graphics · Computer Science 2025-11-04 Andreas Engelhardt , Mark Boss , Vikram Voleti , Chun-Han Yao , Hendrik P. A. Lensch , Varun Jampani

Physics-based differentiable rendering (PBDR) has become an efficient method in computer vision, graphics, and machine learning for addressing an array of inverse problems. PBDR allows patterns to be generated from perceptions which can be…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Preetish Kakkar , Srijani Mukherjee , Hariharan Ragothaman , Vishal Mehta

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

Material creation and reconstruction are crucial for appearance modeling but traditionally require significant time and expertise from artists. While recent methods leverage visual foundation models to synthesize PBR materials from…

Graphics · Computer Science 2025-09-15 Zhi Ying , Boxiang Rong , Jingyu Wang , Maoyuan Xu

Despite advancements in generating visually stunning content, video diffusion models (VDMs) often yield physically inconsistent results due to pixel-only reconstruction. To address this, we propose MMPhysVideo, the first framework to scale…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Shubo Lin , Xuanyang Zhang , Wei Cheng , Weiming Hu , Gang Yu , Jin Gao

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

Realistic indoor or outdoor image synthesis is a core challenge in computer vision and graphics. The learning-based approach is easy to use but lacks physical consistency, while traditional Physically Based Rendering (PBR) offers high…

Graphics · Computer Science 2025-04-25 Yu Guo , Zhiqiang Lao , Xiyun Song , Yubin Zhou , Zongfang Lin , Heather Yu

Multi-view image generation holds significant application value in computer vision, particularly in domains like 3D reconstruction, virtual reality, and augmented reality. Most existing methods, which rely on extending single images, face…

Computer Vision and Pattern Recognition · Computer Science 2025-11-20 Jiaqi Wu , Yaosen Chen , Shuyuan Zhu

4D reconstruction and rendering of human activities is critical for immersive VR/AR experience.Recent advances still fail to recover fine geometry and texture results with the level of detail present in the input images from sparse…

Computer Vision and Pattern Recognition · Computer Science 2021-03-16 Xin Suo , Yuheng Jiang , Pei Lin , Yingliang Zhang , Kaiwen Guo , Minye Wu , Lan Xu