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Related papers: Styl3R: Instant 3D Stylized Reconstruction for Arb…

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Neural reconstruction approaches are rapidly emerging as the preferred representation for 3D scenes, but their limited editability is still posing a challenge. In this work, we propose an approach for 3D scene inpainting -- the task of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Ashkan Mirzaei , Riccardo De Lutio , Seung Wook Kim , David Acuna , Jonathan Kelly , Sanja Fidler , Igor Gilitschenski , Zan Gojcic

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

As demand from the film and gaming industries for 3D scenes with target styles grows, the importance of advanced 3D stylization techniques increases. However, recent methods often struggle to maintain local consistency in color and texture…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Zixiao Gu , Mengtian Li , Ruhua Chen , Zhongxia Ji , Sichen Guo , Zhenye Zhang , Guangnan Ye , Zuo Hu

Class-agnostic 3D instance segmentation tackles the challenging task of segmenting all object instances, including previously unseen ones, without semantic class reliance. Current methods struggle with generalization due to the scarce…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Shengchao Zhou , Jiehong Lin , Jiahui Liu , Shizhen Zhao , Chirui Chang , Xiaojuan Qi

We propose StyleNeRF, a 3D-aware generative model for photo-realistic high-resolution image synthesis with high multi-view consistency, which can be trained on unstructured 2D images. Existing approaches either cannot synthesize…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Jiatao Gu , Lingjie Liu , Peng Wang , Christian Theobalt

Controllable 3D style transfer seeks to restyle a 3D asset so that its textures match a reference image while preserving the integrity and multi-view consistency. The prevalent methods either rely on direct reference style token injection…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Yuteng Ye , Zheng Zhang , Qinchuan Zhang , Di Wang , Youjia Zhang , Wenxiao Zhang , Wei Yang , Yuan Liu

Image stitching aim to align two images taken from different viewpoints into one seamless, wider image. However, when the 3D scene contains depth variations and the camera baseline is significant, noticeable parallax occurs-meaning the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Muhua Zhu , Xinhao Jin , Chengbo Wang , Yongcong Zhang , Yifei Xue , Tie Ji , Yizhen Lao

Reconstructing physically stable 3D scenes from a single RGB image enables casual images to be converted into simulation-ready digital assets for applications such as immersive interaction and content creation. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Xiaoxuan Ma , Jiashun Wang , Nicolas Ugrinovic , Yehonathan Litman , Kris Kitani

We introduce StyleMM, a novel framework that can construct a stylized 3D Morphable Model (3DMM) based on user-defined text descriptions specifying a target style. Building upon a pre-trained mesh deformation network and a texture generator…

Graphics · Computer Science 2025-08-18 Seungmi Lee , Kwan Yun , Junyong Noh

Style transfer is a problem of rendering image with some content in the style of another image, for example a family photo in the style of a painting of some famous artist. The drawback of classical style transfer algorithm is that it…

Computer Vision and Pattern Recognition · Computer Science 2019-06-05 Alexey Schekalev , Victor Kitov

This paper introduces a new method to stylize 3D geometry. The key observation is that the surface normal is an effective instrument to capture different geometric styles. Centered around this observation, we cast stylization as a shape…

Graphics · Computer Science 2021-07-13 Hsueh-Ti Derek Liu , Alec Jacobson

Artistic style transfer aims to use a style image and a content image to synthesize a target image that retains the same artistic expression as the style image while preserving the basic content of the content image. Many recently proposed…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Kunxiao Liu , Guowu Yuan , Hao Wu , Wenhua Qian

In this paper, we show that, a good style representation is crucial and sufficient for generalized style transfer without test-time tuning. We achieve this through constructing a style-aware encoder and a well-organized style dataset called…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Junyao Gao , Yanchen Liu , Yanan Sun , Yinhao Tang , Yanhong Zeng , Kai Chen , Cairong Zhao

Universal Neural Style Transfer (NST) methods are capable of performing style transfer of arbitrary styles in a style-agnostic manner via feature transforms in (almost) real-time. Even though their unimodal parametric style modeling…

Computer Vision and Pattern Recognition · Computer Science 2018-12-03 Paraskevas Pegios , Nikolaos Passalis , Anastasios Tefas

Style transfer is the process of rendering one image with some content in the style of another image, representing the style. Recent studies of Liu et al. (2017) show that traditional style transfer methods of Gatys et al. (2016) and…

Computer Vision and Pattern Recognition · Computer Science 2020-07-09 Victor Kitov , Konstantin Kozlovtsev , Margarita Mishustina

While substantial progresses have been made in automated 2D portrait stylization, admirable 3D portrait stylization from a single user photo remains to be an unresolved challenge. One primary obstacle here is the lack of high quality…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Guoxian Song , Hongyi Xu , Jing Liu , Tiancheng Zhi , Yichun Shi , Jianfeng Zhang , Zihang Jiang , Jiashi Feng , Shen Sang , Linjie Luo

Arbitrary style transfer holds widespread attention in research and boasts numerous practical applications. The existing methods, which either employ cross-attention to incorporate deep style attributes into content attributes or use…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Zhanjie Zhang , Jiakai Sun , Guangyuan Li , Lei Zhao , Quanwei Zhang , Zehua Lan , Haolin Yin , Wei Xing , Huaizhong Lin , Zhiwen Zuo

In this paper, we propose an adaptive keyframe selection method for improved 3D scene reconstruction in dynamic environments. The proposed method integrates two complementary modules: an error-based selection module utilizing photometric…

Robotics · Computer Science 2025-12-30 Raman Jha , Yang Zhou , Giuseppe Loianno

Transferring appearance to 3D assets using different representations of the appearance object - such as images or text - has garnered interest due to its wide range of applications in industries like gaming, augmented reality, and digital…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Sayan Deb Sarkar , Sinisa Stekovic , Vincent Lepetit , Iro Armeni

Conventional 3D style transfer methods rely on a fixed reference image to apply artistic patterns to 3D scenes. However, in practical applications such as virtual or augmented reality, users often prefer more flexible inputs, including…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Xingyu Miao , Xueqi Qiu , Haoran Duan , Yawen Huang , Xian Wu , Jingjing Deng , Yang Long