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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

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

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

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 PacTure, a novel framework for generating physically-based rendering (PBR) material textures for an untextured 3D mesh from a text description. Existing 2D generation-based texturing approaches either generate textures…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Fan Fei , Jiajun Tang , Fei-Peng Tian , Boxin Shi , Ping Tan

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

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

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

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

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

Physically-based rendering (PBR) materials are fundamental to photorealistic graphics, yet their creation remains labor-intensive and requires specialized expertise. While generative models have advanced material synthesis, existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Di Luo , Shuhui Yang , Mingxin Yang , Jiawei Lu , Yixuan Tang , Xintong Han , Zhuo Chen , Beibei Wang , Chunchao Guo

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

3D human motion generation has seen substantial advancement in recent years. While state-of-the-art approaches have improved performance significantly, they still struggle with complex and detailed motions unseen in training data, largely…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Shanlin Sun , Gabriel De Araujo , Jiaqi Xu , Shenghan Zhou , Hanwen Zhang , Ziheng Huang , Chenyu You , Xiaohui Xie

Multi-modal retrieval has seen tremendous progress with the development of vision-language models. However, further improving these models require additional labelled data which is a huge manual effort. In this paper, we propose a framework…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Avinash Madasu , Estelle Aflalo , Gabriela Ben Melech Stan , Shachar Rosenman , Shao-Yen Tseng , Gedas Bertasius , Vasudev Lal

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

We propose a generative framework for producing high-quality PBR textures on a given 3D mesh. As large-scale PBR texture datasets are scarce, our approach focuses on effectively leveraging the embedding space and diffusion priors of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Kyeongmin Yeo , Yunhong Min , Jaihoon Kim , Minhyuk Sung

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

Text-Video Retrieval (TVR) aims to align and associate relevant video content with corresponding natural language queries. Most existing TVR methods are based on large-scale pre-trained vision-language models (e.g., CLIP). However, due to…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Haoran Tang , Meng Cao , Jinfa Huang , Ruyang Liu , Peng Jin , Ge Li , Xiaodan Liang

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…

This paper aims to generate materials for 3D meshes from text descriptions. Unlike existing methods that synthesize texture maps, we propose to generate segment-wise procedural material graphs as the appearance representation, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Shangzan Zhang , Sida Peng , Tao Xu , Yuanbo Yang , Tianrun Chen , Nan Xue , Yujun Shen , Hujun Bao , Ruizhen Hu , Xiaowei Zhou
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