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A fundamental problem in the texturing of 3D meshes using pre-trained text-to-image models is to ensure multi-view consistency. State-of-the-art approaches typically use diffusion models to aggregate multi-view inputs, where common issues…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Zhengyi Zhao , Chen Song , Xiaodong Gu , Yuan Dong , Qi Zuo , Weihao Yuan , Liefeng Bo , Zilong Dong , Qixing Huang

The recent success of pre-trained diffusion models unlocks the possibility of the automatic generation of textures for arbitrary 3D meshes in the wild. However, these models are trained in the screen space, while converting them to a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Hongkun Zhang , Zherong Pan , Congyi Zhang , Lifeng Zhu , Xifeng Gao

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

Texture mapping as a fundamental task in 3D modeling has been well established for well-acquired aerial assets under consistent illumination, yet it remains a challenge when it is scaled to large datasets with images under varying views and…

Computer Vision and Pattern Recognition · Computer Science 2023-07-19 Xiao ling , Rongjun Qin

Recent advances in diffusion models have significantly improved 3D generation, enabling the use of assets generated from an image for embodied AI simulations. However, the one-to-many nature of the image-to-3D problem limits their use due…

Computer Vision and Pattern Recognition · Computer Science 2025-02-26 Onat Şahin , Mohammad Altillawi , George Eskandar , Carlos Carbone , Ziyuan Liu

Reconstructing real-world objects from multi-view images is essential for applications in 3D editing, AR/VR, and digital content creation. Existing methods typically prioritize either geometric accuracy (Multi-View Stereo) or photorealistic…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Zhejia Cai , Puhua Jiang , Shiwei Mao , Hongkun Cao , Ruqi Huang

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

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, 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

3D Gaussian splatting (3DGS) has demonstrated exceptional performance in image-based 3D reconstruction and real-time rendering. However, regions with complex textures require numerous Gaussians to capture significant color variations…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Binxiao Huang , Zhihao Li , Shiyong Liu , Xiao Tang , Jiajun Tang , Jiaqi Lin , Yuxin Cheng , Zhenyu Chen , Xiaofei Wu , Ngai Wong

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

3D scene reconstruction from 2D images has been a long-standing task. Instead of estimating per-frame depth maps and fusing them in 3D, recent research leverages the neural implicit surface as a unified representation for 3D reconstruction.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Xinyi Yu , Liqin Lu , Jintao Rong , Guangkai Xu , Linlin Ou

The advancement of diffusion models has pushed the boundary of text-to-3D object generation. While it is straightforward to composite objects into a scene with reasonable geometry, it is nontrivial to texture such a scene perfectly due to…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Qi Wang , Ruijie Lu , Xudong Xu , Jingbo Wang , Michael Yu Wang , Bo Dai , Gang Zeng , Dan Xu

We present a super-resolution method capable of creating a high-resolution texture map for a virtual 3D object from a set of lower-resolution images of that object. Our architecture unifies the concepts of (i) multi-view super-resolution…

Computer Vision and Pattern Recognition · Computer Science 2020-01-15 Audrey Richard , Ian Cherabier , Martin R. Oswald , Vagia Tsiminaki , Marc Pollefeys , Konrad Schindler

We propose SceneTex, a novel method for effectively generating high-quality and style-consistent textures for indoor scenes using depth-to-image diffusion priors. Unlike previous methods that either iteratively warp 2D views onto a mesh…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Dave Zhenyu Chen , Haoxuan Li , Hsin-Ying Lee , Sergey Tulyakov , Matthias Nießner

Image color consistency is the key problem in digital imaging consistency when creating datasets. Here, we propose an improved 3D Thin-Plate Splines (TPS3D) color correction method to be used, in conjunction with color charts (i.e. Macbeth…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Ismael Benito-Altamirano , David Martínez-Carpena , Hanna Lizarzaburu-Aguilar , Carles Ventura , Cristian Fàbrega , Joan Daniel Prades

Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -video approaches struggle to maintain scene- and object-level consistency beyond a limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Manuel-Andreas Schneider , Angela Dai

Text-driven 3D scene editing has recently attracted increasing attention. Most existing methods follow a render-edit-optimize pipeline, where multi-view images are rendered from a 3D scene, edited with 2D image editors, and then used to…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 Pufan Li , Bi'an Du , Shenghe Zheng , Junyi Yao , Wei Hu

Mesh models have become increasingly accessible for numerous cities; however, the lack of realistic textures restricts their application in virtual urban navigation and autonomous driving. To address this, this paper proposes MeSS…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Xuyang Chen , Zhijun Zhai , Kaixuan Zhou , Zengmao Wang , Jianan He , Dong Wang , Yanfeng Zhang , mingwei Sun , Rüdiger Westermann , Konrad Schindler , Liqiu Meng

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
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