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Texture map production is an important part of 3D modeling and determines the rendering quality. Recently, diffusion-based methods have opened a new way for texture generation. However, restricted control flexibility and limited prompt…

Graphics · Computer Science 2025-06-04 Dongyu Yan , Leyi Wu , Jiantao Lin , Luozhou Wang , Tianshuo Xu , Zhifei Chen , Zhen Yang , Lie Xu , Shunsi Zhang , Yingcong Chen

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

In this work, we address a challenge in video inpainting: reconstructing occluded regions in dynamic, real-world scenarios. Motivated by the need for continuous human motion monitoring in healthcare settings, where facial features are…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zheyan Zhang , Diego Klabjan , Renee CB Manworren

Layout generation is a foundation task of graphic design, which requires the integration of visual aesthetics and harmonious expression of content delivery. However, existing methods still face challenges in generating precise and visually…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Yu Li , Yifan Chen , Gongye Liu , Fei Yin , Qingyan Bai , Jie Wu , Hongfa Wang , Ruihang Chu , Yujiu Yang

Mesh reconstruction from multi-view images is a fundamental problem in computer vision, but its performance degrades significantly under sparse-view conditions, especially in unseen regions where no ground-truth observations are available.…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Haoyang Wang , Liming Liu , Peiheng Wang , Junlin Hao , Jiangkai Wu , Xinggong Zhang

As 3D generation techniques continue to flourish, the demand for generating personalized content is rapidly rising. Users increasingly seek to apply various editing methods to polish generated 3D content, aiming to enhance its color, style,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Weitao Wang , Haoran Xu , Jun Meng , Haoqian Wang

Generating consistent multiple views for 3D reconstruction tasks is still a challenge to existing image-to-3D diffusion models. Generally, incorporating 3D representations into diffusion model decrease the model's speed as well as…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Emmanuelle Bourigault , Pauline Bourigault

This paper presents innovative enhancements to diffusion models by integrating a novel multi-resolution network and time-dependent layer normalization. Diffusion models have gained prominence for their effectiveness in high-fidelity image…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Qihao Liu , Zhanpeng Zeng , Ju He , Qihang Yu , Xiaohui Shen , Liang-Chieh Chen

Motivated by discrete diffusion's success in language-vision modeling, we explore its potential for multi-view generation, a task dominated by continuous approaches. We introduce ViewMask-1-to-3, formulating multi-view synthesis as a…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Ruishu Zhu , Zhihao Huang , Jiacheng Sun , Ping Luo , Hongyuan Zhang , Xuelong Li

This paper addresses the problem of generating textures for 3D mesh assets. Existing approaches often rely on image diffusion models to generate multi-view image observations, which are then transformed onto the mesh surface to produce a…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Xuyang Wang , Ziang Cheng , Zhenyu Li , Jiayu Yang , Haorui Ji , Pan Ji , Mehrtash Harandi , Richard Hartley , Hongdong Li

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

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 Viewset Diffusion, a diffusion-based generator that outputs 3D objects while only using multi-view 2D data for supervision. We note that there exists a one-to-one mapping between viewsets, i.e., collections of several 2D views of…

Computer Vision and Pattern Recognition · Computer Science 2023-09-04 Stanislaw Szymanowicz , Christian Rupprecht , Andrea Vedaldi

Recent advances in generative AI have unveiled significant potential for the creation of 3D content. However, current methods either apply a pre-trained 2D diffusion model with the time-consuming score distillation sampling (SDS), or a…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Yuanxun Lu , Jingyang Zhang , Shiwei Li , Tian Fang , David McKinnon , Yanghai Tsin , Long Quan , Xun Cao , Yao Yao

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

Synthesizing extrapolated views remains a difficult task, especially in urban driving scenes, where the only reliable sources of data are limited RGB captures and sparse LiDAR points. To address this problem, we present PointmapDiff, a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Thang-Anh-Quan Nguyen , Nathan Piasco , Luis Roldão , Moussab Bennehar , Dzmitry Tsishkou , Laurent Caraffa , Jean-Philippe Tarel , Roland Brémond

We introduce MD-ProjTex, a method for fast and consistent text-guided texture generation for 3D shapes using pretrained text-to-image diffusion models. At the core of our approach is a multi-view consistency mechanism in UV space, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Ahmet Burak Yildirim , Mustafa Utku Aydogdu , Duygu Ceylan , Aysegul Dundar

Current methods for 3D scene reconstruction from sparse posed images employ intermediate 3D representations such as neural fields, voxel grids, or 3D Gaussians, to achieve multi-view consistent scene appearance and geometry. In this paper…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Vitor Guizilini , Muhammad Zubair Irshad , Dian Chen , Greg Shakhnarovich , Rares Ambrus

Existing multi-view 3D object reconstruction methods heavily rely on sufficient overlap between input views, where occlusions and sparse coverage in practice frequently yield severe reconstruction incompleteness. Recent advancements in…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Jiahao Chang , Chongjie Ye , Yushuang Wu , Yuantao Chen , Yidan Zhang , Zhongjin Luo , Chenghong Li , Yihao Zhi , Xiaoguang Han

Recent diffusion-based Single-image 3D portrait generation methods typically employ 2D diffusion models to provide multi-view knowledge, which is then distilled into 3D representations. However, these methods usually struggle to produce…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Haoran Wei , Wencheng Han , Xingping Dong , Jianbing Shen