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Related papers: StyleCity: Large-Scale 3D Urban Scenes Stylization

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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

We present Neural 3D Strokes, a novel technique to generate stylized images of a 3D scene at arbitrary novel views from multi-view 2D images. Different from existing methods which apply stylization to trained neural radiance fields at the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Hao-Bin Duan , Miao Wang , Yan-Xun Li , Yong-Liang Yang

We apply style transfer on mesh reconstructions of indoor scenes. This enables VR applications like experiencing 3D environments painted in the style of a favorite artist. Style transfer typically operates on 2D images, making stylization…

Computer Vision and Pattern Recognition · Computer Science 2022-03-18 Lukas Höllein , Justin Johnson , Matthias Nießner

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

We propose Text2Scene, a method to automatically create realistic textures for virtual scenes composed of multiple objects. Guided by a reference image and text descriptions, our pipeline adds detailed texture on labeled 3D geometries in…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Inwoo Hwang , Hyeonwoo Kim , Young Min Kim

3D semantic scene understanding remains a long-standing challenge in the 3D computer vision community. One of the key issues pertains to limited real-world annotated data to facilitate generalizable models. The common practice to tackle…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Duc Nguyen , Yan-Ling Lai , Qilin Zhang , Prabin Gyawali , Benedikt Schwab , Olaf Wysocki , Thomas H. Kolbe

In this work, we aim to address the 3D scene stylization problem - generating stylized images of the scene at arbitrary novel view angles. A straightforward solution is to combine existing novel view synthesis and image/video style transfer…

Computer Vision and Pattern Recognition · Computer Science 2022-01-19 Pei-Ze Chiang , Meng-Shiun Tsai , Hung-Yu Tseng , Wei-sheng Lai , Wei-Chen Chiu

Urban scene reconstruction requires modeling both static infrastructure and dynamic elements while supporting diverse environmental conditions. We present \textbf{StyledStreets}, a multi-style street simulator that achieves…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Yuyin Chen , Yida Wang , Xueyang Zhang , Kun Zhan , Peng Jia , Yifei Zhan , Xianpeng Lang

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

Editable high-fidelity 4D scenes are crucial for autonomous driving, as they can be applied to end-to-end training and closed-loop simulation. However, existing reconstruction methods are primarily limited to replicating observed scenes and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Wenhua Wu , Huai Guan , Zhe Liu , Hesheng Wang

We propose a method to create plausible geometric and texture style variations of 3D objects in the quest to democratize 3D content creation. Given a pair of textured source and target objects, our method predicts a part-aware affine…

Computer Vision and Pattern Recognition · Computer Science 2021-08-31 Kangxue Yin , Jun Gao , Maria Shugrina , Sameh Khamis , Sanja Fidler

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

Recently, a surge of 3D style transfer methods has been proposed that leverage the scene reconstruction power of a pre-trained neural radiance field (NeRF). To successfully stylize a scene this way, one must first reconstruct a…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Y. Wang , A. Gao , Y. Gong , Y. Zeng

Recent advancements in neural representations, such as Neural Radiance Fields and 3D Gaussian Splatting, have increased interest in applying style transfer to 3D scenes. While existing methods can transfer style patterns onto 3D-consistent…

Computer Vision and Pattern Recognition · Computer Science 2025-09-05 Jimin Xu , Bosheng Qin , Tao Jin , Zhou Zhao , Zhenhui Ye , Jun Yu , Fei Wu

Style-guided texture generation aims to generate a texture that is harmonious with both the style of the reference image and the geometry of the input mesh, given a reference style image and a 3D mesh with its text description. Although…

Computer Vision and Pattern Recognition · Computer Science 2024-11-04 Zhiyu Xie , Yuqing Zhang , Xiangjun Tang , Yiqian Wu , Dehan Chen , Gongsheng Li , Xaogang Jin

Visual content creation has spurred a soaring interest given its applications in mobile photography and AR / VR. Style transfer and single-image 3D photography as two representative tasks have so far evolved independently. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Fangzhou Mu , Jian Wang , Yicheng Wu , Yin Li

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

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

We address the challenge of generating 3D worlds from textual descriptions. We propose SynCity, a training- and optimization-free approach, which leverages the geometric precision of pre-trained 3D generative models and the artistic…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Paul Engstler , Aleksandar Shtedritski , Iro Laina , Christian Rupprecht , Andrea Vedaldi

The creation of high-fidelity, customizable 3D indoor scene textures remains a significant challenge. While text-driven methods offer flexibility, they lack the precision for fine-grained, instance-level control, and often produce textures…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Weilin Chen , Jiahao Rao , Wenhao Wang , Xinyang Li , Xuan Cheng , Liujuan Cao
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