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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

We present NaTex, a native texture generation framework that predicts texture color directly in 3D space. In contrast to previous approaches that rely on baking 2D multi-view images synthesized by geometry-conditioned Multi-View Diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Zeqiang Lai , Yunfei Zhao , Zibo Zhao , Xin Yang , Xin Huang , Jingwei Huang , Xiangyu Yue , Chunchao Guo

In recent years, substantial progress has been achieved in learning-based reconstruction of 3D objects. At the same time, generative models were proposed that can generate highly realistic images. However, despite this success in these…

Computer Vision and Pattern Recognition · Computer Science 2019-05-20 Michael Oechsle , Lars Mescheder , Michael Niemeyer , Thilo Strauss , Andreas Geiger

The field of neural rendering has witnessed significant progress with advancements in generative models and differentiable rendering techniques. Though 2D diffusion has achieved success, a unified 3D diffusion pipeline remains unsettled.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Yushi Lan , Fangzhou Hong , Shangchen Zhou , Shuai Yang , Xuyi Meng , Yongwei Chen , Zhaoyang Lyu , Bo Dai , Xingang Pan , Chen Change Loy

Despite the availability of large-scale 3D datasets and advancements in 3D generative models, the complexity and uneven quality of 3D geometry and texture data continue to hinder the performance of 3D generation techniques. In most existing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Xin Yang , Jiantao Lin , Yingjie Xu , Haodong Li , Yingcong Chen

Accurate modeling of 3D objects exhibiting transparency, reflections and thin structures is an extremely challenging problem. Inspired by billboards and geometric proxies used in computer graphics, this paper proposes Generative Latent…

Computer Vision and Pattern Recognition · Computer Science 2020-08-12 Ricardo Martin-Brualla , Rohit Pandey , Sofien Bouaziz , Matthew Brown , Dan B Goldman

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

Recent advancements in 3D generative modeling have significantly improved the generation realism, yet the field is still hampered by existing representations, which struggle to capture assets with complex topologies and detailed appearance.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-17 Jianfeng Xiang , Xiaoxue Chen , Sicheng Xu , Ruicheng Wang , Zelong Lv , Yu Deng , Hongyuan Zhu , Yue Dong , Hao Zhao , Nicholas Jing Yuan , Jiaolong Yang

Latent diffusion models for image generation have crossed a quality threshold which enabled them to achieve mass adoption. Recently, a series of works have made advancements towards replicating this success in the 3D domain, introducing…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Anchit Gupta , Wenhan Xiong , Yixin Nie , Ian Jones , Barlas Oğuz

Automatic 3D facial texture generation has gained significant interest recently. Existing approaches may not support the traditional physically based rendering pipeline or rely on 3D data captured by Light Stage. Our key contribution is a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Chi Wang , Junming Huang , Rong Zhang , Qi Wang , Haotian Yang , Haibin Huang , Chongyang Ma , Weiwei Xu

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

Texture cues on 3D objects are key to compelling visual representations, with the possibility to create high visual fidelity with inherent spatial consistency across different views. Since the availability of textured 3D shapes remains very…

Computer Vision and Pattern Recognition · Computer Science 2022-04-07 Yawar Siddiqui , Justus Thies , Fangchang Ma , Qi Shan , Matthias Nießner , Angela Dai

Generating high-quality 3D assets from text and images has long been challenging, primarily due to the absence of scalable 3D representations capable of capturing intricate geometry distributions. In this work, we introduce Direct3D, a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Shuang Wu , Youtian Lin , Feihu Zhang , Yifei Zeng , Jingxi Xu , Philip Torr , Xun Cao , Yao Yao

Latent 3D reconstruction has shown great promise in empowering 3D semantic understanding and 3D generation by distilling 2D features into the 3D space. However, existing approaches struggle with the domain gap between 2D feature space and…

Computer Vision and Pattern Recognition · Computer Science 2025-02-14 Chaoyi Zhou , Xi Liu , Feng Luo , Siyu Huang

The ability to accurately model random fields plays a critical role in science and engineering for problems involving uncertain, spatially-varying quantities such as heterogeneous material properties and turbulent flows. Deep generative…

Textures are a vital aspect of creating visually appealing and realistic 3D models. In this paper, we study the problem of generating high-fidelity texture given shapes of 3D assets, which has been relatively less explored compared with…

Computer Vision and Pattern Recognition · Computer Science 2023-10-09 An-Chieh Cheng , Xueting Li , Sifei Liu , Xiaolong 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

Texture synthesis is a fundamental problem in computer graphics that would benefit various applications. Existing methods are effective in handling 2D image textures. In contrast, many real-world textures contain meso-structure in the 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Yi-Hua Huang , Yan-Pei Cao , Yu-Kun Lai , Ying Shan , Lin Gao

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

Diffusion models have shown great promise for image generation, beating GANs in terms of generation diversity, with comparable image quality. However, their application to 3D shapes has been limited to point or voxel representations that…

Computer Vision and Pattern Recognition · Computer Science 2022-12-16 Gimin Nam , Mariem Khlifi , Andrew Rodriguez , Alberto Tono , Linqi Zhou , Paul Guerrero
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