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Related papers: StyleMesh: Style Transfer for Indoor 3D Scene Reco…

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We introduce ReStyle3D, a novel framework for scene-level appearance transfer from a single style image to a real-world scene represented by multiple views. The method combines explicit semantic correspondences with multi-view consistency…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Liyuan Zhu , Shengqu Cai , Shengyu Huang , Gordon Wetzstein , Naji Khosravan , Iro Armeni

Stylizing 3D scenes instantly while maintaining multi-view consistency and faithfully resembling a style image remains a significant challenge. Current state-of-the-art 3D stylization methods typically involve computationally intensive…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Peng Wang , Xiang Liu , Peidong Liu

Transferring the style from one image onto another is a popular and widely studied task in computer vision. Yet, style transfer in the 3D setting remains a largely unexplored problem. To our knowledge, we propose the first learning-based…

Computer Vision and Pattern Recognition · Computer Science 2021-05-19 Mattia Segu , Margarita Grinvald , Roland Siegwart , Federico Tombari

We introduce Style Brush, a novel style transfer method for textured meshes designed to empower artists with fine-grained control over the stylization process. Our approach extends traditional 3D style transfer methods by introducing a…

Graphics · Computer Science 2025-10-07 Áron Samuel Kovács , Pedro Hermosilla , Renata G. Raidou

Creating large-scale virtual urban scenes with variant styles is inherently challenging. To facilitate prototypes of virtual production and bypass the need for complex materials and lighting setups, we introduce the first…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Yingshu Chen , Huajian Huang , Tuan-Anh Vu , Ka Chun Shum , Sai-Kit Yeung

In this work, we develop intuitive controls for editing the style of 3D objects. Our framework, Text2Mesh, stylizes a 3D mesh by predicting color and local geometric details which conform to a target text prompt. We consider a disentangled…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Oscar Michel , Roi Bar-On , Richard Liu , Sagie Benaim , Rana Hanocka

We address the new problem of language-guided semantic style transfer of 3D indoor scenes. The input is a 3D indoor scene mesh and several phrases that describe the target scene. Firstly, 3D vertex coordinates are mapped to RGB residues by…

Computer Vision and Pattern Recognition · Computer Science 2022-08-17 Bu Jin , Beiwen Tian , Hao Zhao , Guyue Zhou

Generating high-quality textures for 3D scenes is crucial for applications in interior design, gaming, and augmented/virtual reality (AR/VR). Although recent advancements in 3D generative models have enhanced content creation, significant…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Yunfan Zhang , Zhiwei Xiong , Zhiqi Shen , Guosheng Lin , Hao Wang , Nicolas Vun

3D scene stylization refers to transform the appearance of a 3D scene to match a given style image, ensuring that images rendered from different viewpoints exhibit the same style as the given style image, while maintaining the 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Jiafu Chen , Wei Xing , Jiakai Sun , Tianyi Chu , Yiling Huang , Boyan Ji , Lei Zhao , Huaizhong Lin , Haibo Chen , Zhizhong Wang

The techniques for 3D indoor scene capturing are widely used, but the meshes produced leave much to be desired. In this paper, we propose "RoomDreamer", which leverages powerful natural language to synthesize a new room with a different…

Computer Vision and Pattern Recognition · Computer Science 2023-05-22 Liangchen Song , Liangliang Cao , Hongyu Xu , Kai Kang , Feng Tang , Junsong Yuan , Yang Zhao

Recent advances in text-driven 3D scene editing and stylization, which leverage the powerful capabilities of 2D generative models, have demonstrated promising outcomes. However, challenges remain in ensuring high-quality stylization and…

Graphics · Computer Science 2026-03-03 Haruo Fujiwara , Yusuke Mukuta , Tatsuya Harada

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

We propose a simple yet effective pipeline for stylizing a 3D scene, harnessing the power of 2D image diffusion models. Given a NeRF model reconstructed from a set of multi-view images, we perform 3D style transfer by refining the source…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Haruo Fujiwara , Yusuke Mukuta , Tatsuya Harada

Style transfer is a problem of rendering a content image in the style of another style image. A natural and common practical task in applications of style transfer is to adjust the strength of stylization. Algorithm of Gatys et al. (2016)…

Computer Vision and Pattern Recognition · Computer Science 2019-04-19 Victor Kitov

Transferring artistic styles onto everyday photographs has become an extremely popular task in both academia and industry. Recently, offline training has replaced on-line iterative optimization, enabling nearly real-time stylization. When…

Computer Vision and Pattern Recognition · Computer Science 2017-12-01 Xin Wang , Geoffrey Oxholm , Da Zhang , Yuan-Fang Wang

3D content creation via text-driven stylization has played a fundamental challenge to multimedia and graphics community. Recent advances of cross-modal foundation models (e.g., CLIP) have made this problem feasible. Those approaches…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Haibo Yang , Yang Chen , Yingwei Pan , Ting Yao , Zhineng Chen , Tao Mei

Neural Radiance Fields (NeRF) have emerged as a powerful tool for creating highly detailed and photorealistic scenes. Existing methods for NeRF-based 3D style transfer need extensive per-scene optimization for single or multiple styles,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Adil Meric , Umut Kocasari , Matthias Nießner , Barbara Roessle

Shape and geometric patterns are essential in defining stylistic identity. However, current 3D style transfer methods predominantly focus on transferring colors and textures, often overlooking geometric aspects. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Hyunyoung Jung , Seonghyeon Nam , Nikolaos Sarafianos , Sungjoo Yoo , Alexander Sorkine-Hornung , Rakesh Ranjan

3D scenes photorealistic stylization aims to generate photorealistic images from arbitrary novel views according to a given style image while ensuring consistency when rendering from different viewpoints. Some existing stylization methods…

Computer Vision and Pattern Recognition · Computer Science 2022-08-23 Yaosen Chen , Qi Yuan , Zhiqiang Li , Yuegen Liu , Wei Wang , Chaoping Xie , Xuming Wen , Qien Yu

3D pose transfer is one of the most challenging 3D generation tasks. It aims to transfer the pose of a source mesh to a target mesh and keep the identity (e.g., body shape) of the target mesh. Some previous works require key point…

Computer Vision and Pattern Recognition · Computer Science 2021-12-28 Chaoyue Song , Jiacheng Wei , Ruibo Li , Fayao Liu , Guosheng Lin
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