English
Related papers

Related papers: TexRO: Generating Delicate Textures of 3D Models b…

200 papers

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

Given a 3D mesh, we aim to synthesize 3D textures that correspond to arbitrary textual descriptions. Current methods for generating and assembling textures from sampled views often result in prominent seams or excessive smoothing. To tackle…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Dong Huo , Zixin Guo , Xinxin Zuo , Zhihao Shi , Juwei Lu , Peng Dai , Songcen Xu , Li Cheng , Yee-Hong Yang

In this work, we focus on synthesizing high-quality textures on 3D meshes. We present Point-UV diffusion, a coarse-to-fine pipeline that marries the denoising diffusion model with UV mapping to generate 3D consistent and high-quality…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Xin Yu , Peng Dai , Wenbo Li , Lan Ma , Zhengzhe Liu , Xiaojuan Qi

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

We present a new pipeline for acquiring a textured mesh in the wild with a single smartphone which offers access to images, depth maps, and valid poses. Our method first introduces an RGBD-aided structure from motion, which can yield…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Jaehoon Choi , Dongki Jung , Taejae Lee , Sangwook Kim , Youngdong Jung , Dinesh Manocha , Donghwan Lee

Incremental scene reconstruction is essential to the navigation in robotics. Most of the conventional methods typically make use of either TSDF (truncated signed distance functions) volume or neural networks to implicitly represent the…

Robotics · Computer Science 2024-04-30 Shaofan Liu , Junbo Chen , Jianke Zhu

High-quality 3D texture generation remains a fundamental challenge due to the view-inconsistency inherent in current mainstream multi-view diffusion pipelines. Existing representations either rely on UV maps, which suffer from distortion…

Computer Vision and Pattern Recognition · Computer Science 2026-02-17 Ziteng Lu , Yushuang Wu , Chongjie Ye , Yuda Qiu , Jing Shao , Xiaoyang Guo , Jiaqing Zhou , Tianlei Hu , Kun Zhou , Xiaoguang Han

We present UniTEX, a novel two-stage 3D texture generation framework to create high-quality, consistent textures for 3D assets. Existing approaches predominantly rely on UV-based inpainting to refine textures after reprojecting the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Yixun Liang , Kunming Luo , Xiao Chen , Rui Chen , Hongyu Yan , Weiyu Li , Jiarui Liu , Ping Tan

Neural Radiance Fields (NeRF) have constituted a remarkable breakthrough in image-based 3D reconstruction. However, their implicit volumetric representations differ significantly from the widely-adopted polygonal meshes and lack support…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Jiaxiang Tang , Hang Zhou , Xiaokang Chen , Tianshu Hu , Errui Ding , Jingdong Wang , Gang Zeng

Text-to-texture generation has recently attracted increasing attention, but existing methods often suffer from the problems of view inconsistencies, apparent seams, and misalignment between textures and the underlying mesh. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Jangyeong Kim , Donggoo Kang , Junyoung Choi , Jeonga Wi , Junho Gwon , Jiun Bae , Dumim Yoon , Junghyun Han

Existing UV mapping algorithms are designed to operate on well-behaved meshes, instead of the geometry representations produced by state-of-the-art 3D reconstruction and generation techniques. As such, applying these methods to the volume…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Pratul P. Srinivasan , Stephan J. Garbin , Dor Verbin , Jonathan T. Barron , Ben Mildenhall

We present TexFusion (Texture Diffusion), a new method to synthesize textures for given 3D geometries, using large-scale text-guided image diffusion models. In contrast to recent works that leverage 2D text-to-image diffusion models to…

Computer Vision and Pattern Recognition · Computer Science 2023-10-24 Tianshi Cao , Karsten Kreis , Sanja Fidler , Nicholas Sharp , Kangxue Yin

Texture reconstruction techniques generally suffer from the errors in keyframe poses. We present a non-iterative method for seamless texture reconstruction of a given 3D scene. Our method finds the best texture alignment in a single shot…

Computer Vision and Pattern Recognition · Computer Science 2020-11-03 Mohammad Rouhani , Matthieu Fradet , Caroline Baillard

We present TexMesh, a novel approach to reconstruct detailed human meshes with high-resolution full-body texture from RGB-D video. TexMesh enables high quality free-viewpoint rendering of humans. Given the RGB frames, the captured…

Computer Vision and Pattern Recognition · Computer Science 2020-09-22 Tiancheng Zhi , Christoph Lassner , Tony Tung , Carsten Stoll , Srinivasa G. Narasimhan , Minh Vo

Texturing is a fundamental process in computer graphics. Texture is leveraged to enhance the visualization outcome for a 3D scene. In many cases a texture image cannot cover a large 3D model surface because of its small resolution.…

Computer Vision and Pattern Recognition · Computer Science 2021-03-16 Vasilis Toulatzis , Ioannis Fudos

We present Text2Tex, a novel method for generating high-quality textures for 3D meshes from the given text prompts. Our method incorporates inpainting into a pre-trained depth-aware image diffusion model to progressively synthesize high…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Dave Zhenyu Chen , Yawar Siddiqui , Hsin-Ying Lee , Sergey Tulyakov , Matthias Nießner

Seams, distortions, wasted UV space, vertex-duplication, and varying resolution over the surface are the most prominent issues of the standard UV-based texturing of meshes. These issues are particularly acute when automatic UV-unwrapping…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Simone Foti , Stefanos Zafeiriou , Tolga Birdal

3D meshes are widely used in computer vision and graphics for their efficiency in animation and minimal memory use, playing a crucial role in movies, games, AR, and VR. However, creating temporally consistent and realistic textures for mesh…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Jingzhi Bao , Xueting Li , Ming-Hsuan Yang

Given a 3D mesh with a UV parameterization, we introduce a novel approach to generating textures from text prompts. While prior work uses optimization from Text-to-Image Diffusion models to generate textures and geometry, this is slow and…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Julian Knodt , Xifeng Gao

Prevailing 3D texture generation methods, which often rely on multi-view fusion, are frequently hindered by inter-view inconsistencies and incomplete coverage of complex surfaces, limiting the fidelity and completeness of the generated…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Yifei Zeng , Yajie Bao , Jiachen Qian , Shuang Wu , Youtian Lin , Hao Zhu , Buyu Li , Feihu Zhang , Xun Cao , Yao Yao
‹ Prev 1 2 3 10 Next ›