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Related papers: 3DTextureTransformer: Geometry Aware Texture Gener…

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Textured 3D morphing creates smooth and plausible interpolation sequences between two 3D objects, focusing on transitions in both shape and texture. This is important for creative applications like visual effects in filmmaking. Previous…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Songlin Yang , Yushi Lan , Honghua Chen , Xingang Pan

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 ShaDDR, an example-based deep generative neural network which produces a high-resolution textured 3D shape through geometry detailization and conditional texture generation applied to an input coarse voxel shape. Trained on a…

Computer Vision and Pattern Recognition · Computer Science 2023-11-23 Qimin Chen , Zhiqin Chen , Hang Zhou , Hao Zhang

Geometry and texture estimation from a single face image is an ill-posed problem since there is very little information to work with. The problem further escalates when the face is rotated at a different angle. This paper tries to tackle…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Rohit Das , Tzung-Han Lin , Ko-Chih Wang

3D terrain models are essential in fields such as video game development and film production. Since surface color often correlates with terrain geometry, capturing this relationship is crucial to achieving realism. However, most existing…

Graphics · Computer Science 2025-12-18 Kazuki Higo , Toshiki Kanai , Yuki Endo , Yoshihiro Kanamori

3D generative modeling is accelerating as the technology allowing the capture of geometric data is developing. However, the acquired data is often inconsistent, resulting in unregistered meshes or point clouds. Many generative learning…

Computer Vision and Pattern Recognition · Computer Science 2023-06-29 Thomas Besnier , Sylvain Arguillère , Emery Pierson , Mohamed Daoudi

Transferring 2D textures onto complex 3D scenes plays a vital role in enhancing the efficiency and controllability of 3D multimedia content creation. However, existing 3D style transfer methods primarily focus on transferring abstract…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Wenjie Liu , Zhongliang Liu , Junwei Shu , Changbo Wang , Yang Li

We study the problem of 3D-aware full-body human generation, aiming at creating animatable human avatars with high-quality textures and geometries. Generally, two challenges remain in this field: i) existing methods struggle to generate…

Computer Vision and Pattern Recognition · Computer Science 2023-10-05 Xuanmeng Zhang , Jianfeng Zhang , Rohan Chacko , Hongyi Xu , Guoxian Song , Yi Yang , Jiashi Feng

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

Inspired by generative paradigms in image and video, 3D shape generation has made notable progress, enabling the rapid synthesis of high-fidelity 3D assets from a single image. However, current methods still face challenges, including the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Yangguang Li , Xianglong He , Zi-Xin Zou , Zexiang Liu , Wanli Ouyang , Ding Liang , Yan-Pei Cao

We introduce a framework for intrinsic latent diffusion models operating directly on the surfaces of 3D shapes, with the goal of synthesizing high-quality textures. Our approach is underpinned by two contributions: field latents, a latent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Thomas W. Mitchel , Carlos Esteves , Ameesh Makadia

Reconstructing the 3D mesh of a general object from a single image is now possible thanks to the latest advances of deep learning technologies. However, due to the nontrivial difficulty of generating a feasible mesh structure, the…

Computer Vision and Pattern Recognition · Computer Science 2019-09-04 Junyi Pan , Xiaoguang Han , Weikai Chen , Jiapeng Tang , Kui Jia

Textured meshes significantly enhance the realism and detail of objects by mapping intricate texture details onto the geometric structure of 3D models. This advancement is valuable across various applications, including entertainment,…

Graphics · Computer Science 2024-12-12 Kaiwei Zhang , Dandan Zhu , Xiongkuo Min , Guangtao Zhai

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

Recent advances in diffusion models have demonstrated exceptional capabilities in image and video generation, further improving the effectiveness of 4D synthesis. Existing 4D generation methods can generate high-quality 4D objects or scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Bohan Zeng , Ling Yang , Siyu Li , Jiaming Liu , Zixiang Zhang , Juanxi Tian , Kaixin Zhu , Yongzhen Guo , Fu-Yun Wang , Minkai Xu , Stefano Ermon , Wentao Zhang

This paper presents Paint3D, a novel coarse-to-fine generative framework that is capable of producing high-resolution, lighting-less, and diverse 2K UV texture maps for untextured 3D meshes conditioned on text or image inputs. The key…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Xianfang Zeng , Xin Chen , Zhongqi Qi , Wen Liu , Zibo Zhao , Zhibin Wang , Bin Fu , Yong Liu , Gang Yu

Texture synthesis is a fundamental task in computer vision, whose goal is to generate visually realistic and structurally coherent textures for a wide range of applications, from graphics to scientific simulations. While traditional methods…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Elahe Salari , Zohreh Azimifar

In the past several decades, many attempts have been made to model synthetic realistic geometric data. The goal of such models is to generate plausible 3D geometries and textures. Perhaps the best known of its kind is the linear 3D…

Computational Geometry · Computer Science 2018-08-28 Ron Slossberg , Gil Shamai , Ron Kimmel

Despite recent advances in geometric modeling, 3D mesh modeling still involves a considerable amount of manual labor by experts. In this paper, we introduce Mesh Draping: a neural method for transferring existing mesh structure from one…

Graphics · Computer Science 2021-10-12 Amir Hertz , Or Perel , Raja Giryes , Olga Sorkine-Hornung , Daniel Cohen-Or

Applications in virtual and augmented reality create a demand for rapid creation and easy access to large sets of 3D models. An effective way to address this demand is to edit or deform existing 3D models based on a reference, e.g., a 2D…

Computer Vision and Pattern Recognition · Computer Science 2019-03-11 Weiyue Wang , Duygu Ceylan , Radomir Mech , Ulrich Neumann