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Related papers: VideoMat: Extracting PBR Materials from Video Diff…

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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

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…

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

Creating photorealistic materials for 3D rendering requires exceptional artistic skill. Generative models for materials could help, but are currently limited by the lack of high-quality training data. While recent video generative models…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Bowen Xue , Saeed Hadadan , Zheng Zeng , Fabrice Rousselle , Zahra Montazeri , Milos Hasan

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 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 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

Diffusion models have emerged as a powerful generative method for synthesizing high-quality and diverse set of images. In this paper, we propose a video generation method based on diffusion models, where the effects of motion are modeled in…

Computer Vision and Pattern Recognition · Computer Science 2022-12-02 Kangfu Mei , Vishal M. Patel

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 temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial…

Computer Vision and Pattern Recognition · Computer Science 2022-06-24 Jonathan Ho , Tim Salimans , Alexey Gritsenko , William Chan , Mohammad Norouzi , David J. Fleet

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

Video inpainting is the task of filling a region in a video in a visually convincing manner. It is very challenging due to the high dimensionality of the data and the temporal consistency required for obtaining convincing results. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Nicolas Cherel , Andrés Almansa , Yann Gousseau , Alasdair Newson

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

Decomposing physically-based materials from images into their constituent properties remains challenging, particularly when maintaining both computational efficiency and physical consistency. While recent diffusion-based approaches have…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Yijia Hong , Yuan-Chen Guo , Ran Yi , Yulong Chen , Yan-Pei Cao , Lizhuang Ma

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

We present Intrinsic Image Diffusion, a generative model for appearance decomposition of indoor scenes. Given a single input view, we sample multiple possible material explanations represented as albedo, roughness, and metallic maps.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Peter Kocsis , Vincent Sitzmann , Matthias Nießner

In recent years, video generation has seen significant advancements. However, challenges still persist in generating complex motions and interactions. To address these challenges, we introduce ReVision, a plug-and-play framework that…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Qihao Liu , Ju He , Qihang Yu , Liang-Chieh Chen , Alan Yuille

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

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

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
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