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Recently, text-guided image editing has achieved significant success. However, existing methods can only apply simple textures like wood or gold when changing the texture of an object. Complex textures such as cloud or fire pose a…

Computer Vision and Pattern Recognition · Computer Science 2025-01-15 Zihan Su , Junhao Zhuang , Chun Yuan

We present TextureDreamer, a novel image-guided texture synthesis method to transfer relightable textures from a small number of input images (3 to 5) to target 3D shapes across arbitrary categories. Texture creation is a pivotal challenge…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Yu-Ying Yeh , Jia-Bin Huang , Changil Kim , Lei Xiao , Thu Nguyen-Phuoc , Numair Khan , Cheng Zhang , Manmohan Chandraker , Carl S Marshall , Zhao Dong , Zhengqin Li

We introduce TexVerse, a large-scale 3D dataset featuring high-resolution textures. While recent advances in large-scale 3D datasets have enhanced high-resolution geometry generation, creating high-resolution textures end-to-end remains…

Computer Vision and Pattern Recognition · Computer Science 2025-09-05 Yibo Zhang , Li Zhang , Rui Ma , Nan Cao

We consider the task of generating realistic 3D shapes, which is useful for a variety of applications such as automatic scene generation and physical simulation. Compared to other 3D representations like voxels and point clouds, meshes are…

Graphics · Computer Science 2023-04-18 Zhen Liu , Yao Feng , Michael J. Black , Derek Nowrouzezahrai , Liam Paull , Weiyang Liu

An explainable, efficient and lightweight method for texture generation, called TGHop (an acronym of Texture Generation PixelHop), is proposed in this work. Although synthesis of visually pleasant texture can be achieved by deep neural…

Computer Vision and Pattern Recognition · Computer Science 2021-07-09 Xuejing Lei , Ganning Zhao , Kaitai Zhang , C. -C. Jay Kuo

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

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

Node graph systems are used ubiquitously for material design in computer graphics. They allow the use of visual programming to achieve desired effects without writing code. As high-level design tools they provide convenience and…

Graphics · Computer Science 2023-04-27 Yiwei Hu , Paul Guerrero , Miloš Hašan , Holly Rushmeier , Valentin Deschaintre

Recently, diffusion-based deep generative models (e.g., Stable Diffusion) have shown impressive results in text-to-image synthesis. However, current text-to-image models often require multiple passes of prompt engineering by humans in order…

Computation and Language · Computer Science 2023-11-14 Tingfeng Cao , Chengyu Wang , Bingyan Liu , Ziheng Wu , Jinhui Zhu , Jun Huang

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

Texture and material blending is one of the leading methods for adding variety to rendered virtual worlds, creating composite materials, and generating procedural content. When done naively, it can introduce either visible seams or contrast…

Graphics · Computer Science 2025-02-20 Bartlomiej Wronski

We propose Text2Scene, a method to automatically create realistic textures for virtual scenes composed of multiple objects. Guided by a reference image and text descriptions, our pipeline adds detailed texture on labeled 3D geometries in…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Inwoo Hwang , Hyeonwoo Kim , Young Min Kim

Generating high-quality, photorealistic textures for 3D human avatars remains a fundamental yet challenging task in computer vision and multimedia field. However, real paired front and back images of human subjects are rarely available with…

Graphics · Computer Science 2026-04-10 Mingxiao Tu , Shuchang Ye , Hoijoon Jung , Jinman Kim

The text-to-image synthesis by diffusion models has recently shown remarkable performance in generating high-quality images. Although performs well for simple texts, the models may get confused when faced with complex texts that contain…

Computer Vision and Pattern Recognition · Computer Science 2024-01-15 Chang Yu , Junran Peng , Xiangyu Zhu , Zhaoxiang Zhang , Qi Tian , Zhen Lei

We introduce TM-NET, a novel deep generative model for synthesizing textured meshes in a part-aware manner. Once trained, the network can generate novel textured meshes from scratch or predict textures for a given 3D mesh, without image…

Graphics · Computer Science 2021-06-10 Lin Gao , Tong Wu , Yu-Jie Yuan , Ming-Xian Lin , Yu-Kun Lai , Hao Zhang

Recently, the surge of efficient and automated 3D AI-generated content (AIGC) methods has increasingly illuminated the path of transforming human imagination into complex 3D structures. However, the automated generation of 3D content is…

Graphics · Computer Science 2024-12-20 Pei Chen , Fudong Wang , Yixuan Tong , Jingdong Chen , Ming Yang , Minghui Yang

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

Textured high-fidelity 3D models are crucial for games, AR/VR, and film, but human-aligned evaluation methods still fall behind despite recent advances in 3D reconstruction and generation. Existing metrics, such as Chamfer Distance, often…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Tianyu Luan , Xuelu Feng , Zixin Zhu , Phani Nuney , Sheng Liu , Xuan Gong , David Doermann , Chunming Qiao , Junsong Yuan

This paper presents a method to reconstruct high-quality textured 3D models from both multi-view and single-view images. The reconstruction is posed as an adaptation problem and is done progressively where in the first stage, we focus on…

Computer Vision and Pattern Recognition · Computer Science 2022-03-18 Aysegul Dundar , Jun Gao , Andrew Tao , Bryan Catanzaro

Text-to-image generation models have seen considerable advancement, catering to the increasing interest in personalized image creation. Current customization techniques often necessitate users to provide multiple images (typically 3-5) for…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Linhao Zhong , Yan Hong , Wentao Chen , Binglin Zhou , Yiyi Zhang , Jianfu Zhang , Liqing Zhang
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