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相关论文: M2StyleGS: Multi-Modality 3D Style Transfer with G…

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Gaussian Splatting (GS) has recently emerged as an efficient representation for rendering 3D scenes from 2D images and has been extended to images, videos, and dynamic 4D content. However, applying style transfer to GS-based…

计算机视觉与模式识别 · 计算机科学 2025-10-27 Kornel Howil , Joanna Waczyńska , Piotr Borycki , Tadeusz Dziarmaga , Marcin Mazur , Przemysław Spurek

In recent years, there has been a growing demand to stylize a given 3D scene to align with the artistic style of reference images for creative purposes. While 3D Gaussian Splatting(GS) has emerged as a promising and efficient method for…

计算机视觉与模式识别 · 计算机科学 2025-06-10 Yangkai Lin , Jiabao Lei , Kui jia

We introduce StyleGaussian, a novel 3D style transfer technique that allows instant transfer of any image's style to a 3D scene at 10 frames per second (fps). Leveraging 3D Gaussian Splatting (3DGS), StyleGaussian achieves style transfer…

计算机视觉与模式识别 · 计算机科学 2024-03-13 Kunhao Liu , Fangneng Zhan , Muyu Xu , Christian Theobalt , Ling Shao , Shijian Lu

3D scene stylization extends the work of neural style transfer to 3D. A vital challenge in this problem is to maintain the uniformity of the stylized appearance across multiple views. A vast majority of the previous works achieve this by…

计算机视觉与模式识别 · 计算机科学 2024-09-09 Abhishek Saroha , Mariia Gladkova , Cecilia Curreli , Dominik Muhle , Tarun Yenamandra , Daniel Cremers

3D neural style transfer has gained significant attention for its potential to provide user-friendly stylization with spatial consistency. However, existing 3D style transfer methods often fall short in terms of inference efficiency,…

计算机视觉与模式识别 · 计算机科学 2024-10-15 Wanlin Liang , Hongbin Xu , Weitao Chen , Feng Xiao , Wenxiong Kang

Recent advancements in radiance fields have opened new avenues for creating high-quality 3D assets and scenes. Style transfer can enhance these 3D assets with diverse artistic styles, transforming creative expression. However, existing…

计算机视觉与模式识别 · 计算机科学 2024-07-15 Sahil Jain , Avik Kuthiala , Prabhdeep Singh Sethi , Prakanshul Saxena

We present InstantStyleGaussian, an innovative 3D style transfer method based on the 3D Gaussian Splatting (3DGS) scene representation. By inputting a target-style image, it quickly generates new 3D GS scenes. Our method operates on…

计算机视觉与模式识别 · 计算机科学 2024-08-27 Xin-Yi Yu , Jun-Xin Yu , Li-Bo Zhou , Yan Wei , Lin-Lin Ou

Applying style transfer to a full 3D environment is a challenging task that has seen many developments since the advent of neural rendering. 3D Gaussian splatting (3DGS) has recently pushed further many limits of neural rendering in terms…

计算机视觉与模式识别 · 计算机科学 2025-04-11 Bruno Galerne , Jianling Wang , Lara Raad , Jean-Michel Morel

We introduce G-Style, a novel algorithm designed to transfer the style of an image onto a 3D scene represented using Gaussian Splatting. Gaussian Splatting is a powerful 3D representation for novel view synthesis, as -- compared to other…

图形学 · 计算机科学 2024-09-06 Áron Samuel Kovács , Pedro Hermosilla , Renata G. Raidou

3D Gaussian Splatting (3DGS) has recently emerged as a fast, high-quality method for novel view synthesis (NVS). However, its use of low-degree spherical harmonics limits its ability to capture spatially varying color and view-dependent…

计算机视觉与模式识别 · 计算机科学 2025-11-19 Hoang Chuong Nguyen , Wei Mao , Jose M. Alvarez , Miaomiao Liu

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…

计算机视觉与模式识别 · 计算机科学 2025-09-05 Jimin Xu , Bosheng Qin , Tao Jin , Zhou Zhao , Zhenhui Ye , Jun Yu , Fei Wu

As XR technology continues to advance rapidly, 3D generation and editing are increasingly crucial. Among these, stylization plays a key role in enhancing the appearance of 3D models. By utilizing stylization, users can achieve consistent…

计算机视觉与模式识别 · 计算机科学 2025-09-03 Dingxi Zhang , Yu-Jie Yuan , Zhuoxun Chen , Fang-Lue Zhang , Zhenliang He , Shiguang Shan , Lin Gao

Referenced-based scene stylization that edits the appearance based on a content-aligned reference image is an emerging research area. Starting with a pretrained neural radiance field (NeRF), existing methods typically learn a novel…

计算机视觉与模式识别 · 计算机科学 2024-07-11 Yiqun Mei , Jiacong Xu , Vishal M. Patel

Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising method, producing high-quality renderings of scenes and enabling…

计算机视觉与模式识别 · 计算机科学 2024-07-19 Richard Shaw , Michal Nazarczuk , Jifei Song , Arthur Moreau , Sibi Catley-Chandar , Helisa Dhamo , Eduardo Perez-Pellitero

We present Stylos, a single-forward 3D Gaussian framework for 3D style transfer that operates on unposed content, from a single image to a multi-view collection, conditioned on a separate reference style image. Stylos synthesizes a stylized…

计算机视觉与模式识别 · 计算机科学 2026-03-03 Hanzhou Liu , Jia Huang , Mi Lu , Srikanth Saripalli , Peng Jiang

Recovering 3D information from scenes via multi-view stereo reconstruction (MVS) and novel view synthesis (NVS) is inherently challenging, particularly in scenarios involving sparse-view setups. The advent of 3D Gaussian Splatting (3DGS)…

计算机视觉与模式识别 · 计算机科学 2025-05-06 Shubhendu Jena , Shishir Reddy Vutukur , Adnane Boukhayma

We present FPGS, a feed-forward photorealistic style transfer method of large-scale radiance fields represented by Gaussian Splatting. FPGS, stylizes large-scale 3D scenes with arbitrary, multiple style reference images without additional…

图形学 · 计算机科学 2025-03-14 GeonU Kim , Kim Youwang , Lee Hyoseok , Tae-Hyun Oh

In the rapidly evolving field of 3D reconstruction, 3D Gaussian Splatting (3DGS) and 2D Gaussian Splatting (2DGS) represent significant advancements. Although 2DGS compresses 3D Gaussian primitives into 2D Gaussian surfels to effectively…

计算机视觉与模式识别 · 计算机科学 2024-07-17 Zhuoxiao Li , Shanliang Yao , Yijie Chu , Angel F. Garcia-Fernandez , Yong Yue , Eng Gee Lim , Xiaohui Zhu

3D style transfer enables the creation of visually expressive 3D content, enriching the visual appearance of 3D scenes and objects. However, existing VGG- and CLIP-based methods struggle to model multi-view consistency within the model…

计算机视觉与模式识别 · 计算机科学 2026-01-28 Yitong Yang , Xuexin Liu , Yinglin Wang , Jing Wang , Hao Dou , Changshuo Wang , Shuting He

Recent advancements in 3D editing have highlighted the potential of text-driven methods in real-time, user-friendly AR/VR applications. However, current methods rely on 2D diffusion models without adequately considering multi-view…

计算机视觉与模式识别 · 计算机科学 2025-04-21 Dong In Lee , Hyeongcheol Park , Jiyoung Seo , Eunbyung Park , Hyunje Park , Ha Dam Baek , Sangheon Shin , Sangmin Kim , Sangpil Kim
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