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Related papers: StyleGaussian: Instant 3D Style Transfer with Gaus…

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3D style transfer refers to the artistic stylization of 3D assets based on reference style images. Recently, 3DGS-based stylization methods have drawn considerable attention, primarily due to their markedly enhanced training and rendering…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Yian Zhao , Rushi Ye , Ruochong Zheng , Zesen Cheng , Chaoran Feng , Jiashu Yang , Pengchong Qiao , Chang Liu , Jie Chen

The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the rendering speed of novel view synthesis. Unlike neural implicit representations like Neural Radiance Fields (NeRF) that represent a 3D scene with position and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Tong Wu , Yu-Jie Yuan , Ling-Xiao Zhang , Jie Yang , Yan-Pei Cao , Ling-Qi Yan , Lin Gao

Transferring 2D textures onto complex 3D scenes plays a vital role in enhancing the efficiency and controllability of 3D multimedia content creation. However, existing 3D style transfer methods primarily focus on transferring abstract…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Wenjie Liu , Zhongliang Liu , Junwei Shu , Changbo Wang , Yang Li

Recent advancements in dynamic 3D scene reconstruction have shown promising results, enabling high-fidelity 3D novel view synthesis with improved temporal consistency. Among these, 4D Gaussian Splatting (4DGS) has emerged as an appealing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Seungjun Oh , Younggeun Lee , Hyejin Jeon , Eunbyung Park

3D Gaussian Splatting (3DGS) enables high-quality rendering of 3D scenes and is getting increasing adoption in domains like autonomous driving and embodied intelligence. However, 3DGS still faces major efficiency challenges when faced with…

Hardware Architecture · Computer Science 2025-07-31 Linye Wei , Jiajun Tang , Fan Fei , Boxin Shi , Runsheng Wang , Meng Li

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…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Hoang Chuong Nguyen , Wei Mao , Jose M. Alvarez , Miaomiao Liu

Recent advances in 3D content creation mostly leverage optimization-based 3D generation via score distillation sampling (SDS). Though promising results have been exhibited, these methods often suffer from slow per-sample optimization,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jiaxiang Tang , Jiawei Ren , Hang Zhou , Ziwei Liu , Gang Zeng

Reconstructing deformable tissues from endoscopic videos is essential in many downstream surgical applications. However, existing methods suffer from slow rendering speed, greatly limiting their practical use. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Yifan Liu , Chenxin Li , Chen Yang , Yixuan Yuan

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…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Hanzhou Liu , Jia Huang , Mi Lu , Srikanth Saripalli , Peng Jiang

Recent advancements in 3D reconstruction from single images have been driven by the evolution of generative models. Prominent among these are methods based on Score Distillation Sampling (SDS) and the adaptation of diffusion models in the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Zi-Xin Zou , Zhipeng Yu , Yuan-Chen Guo , Yangguang Li , Ding Liang , Yan-Pei Cao , Song-Hai Zhang

Novel view synthesis of dynamic scenes has been an intriguing yet challenging problem. Despite recent advancements, simultaneously achieving high-resolution photorealistic results, real-time rendering, and compact storage remains a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Zhan Li , Zhang Chen , Zhong Li , Yi Xu

In the domain of 3D scene representation, 3D Gaussian Splatting (3DGS) has emerged as a pivotal technology. However, its application to large-scale, high-resolution scenes (exceeding 4k$\times$4k pixels) is hindered by the excessive…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Wenkai Liu , Tao Guan , Bin Zhu , Lili Ju , Zikai Song , Dan Li , Yuesong Wang , Wei Yang

Stylizing a dynamic scene based on an exemplar image is critical for various real-world applications, including gaming, filmmaking, and augmented and virtual reality. However, achieving consistent stylization across both spatial and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-08 Abhishek Saroha , Florian Hofherr , Mariia Gladkova , Cecilia Curreli , Or Litany , Daniel Cremers

3D Gaussian splatting (3DGS) is an innovative rendering technique that surpasses the neural radiance field (NeRF) in both rendering speed and visual quality by leveraging an explicit 3D scene representation. Existing 3DGS approaches require…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Lintao Xiang , Hongpei Zheng , Yating Huang , Qijun Yang , Hujun Yin

3D Gaussian Splatting (3DGS) has emerged as a novel explicit representation for 3D scenes, offering both high-fidelity reconstruction and efficient rendering. However, 3DGS lacks 3D segmentation ability, which limits its applicability in…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Yupeng Zhang , Dezhi Zheng , Ping Lu , Han Zhang , Lei Wang , Liping xiang , Cheng Luo , Kaijun Deng , Xiaowen Fu , Linlin Shen , Jinbao Wang

3D Gaussian Splatting (3DGS) has recently gained popularity for efficient scene rendering by representing scenes as explicit sets of anisotropic 3D Gaussians. However, most existing work focuses primarily on modeling external surfaces. In…

Image and Video Processing · Electrical Eng. & Systems 2026-01-12 Shuxin Liang , Yihan Xiao , Wenlu Tang

Capturing and reconstructing high-speed dynamic 3D scenes has numerous applications in computer graphics, vision, and interdisciplinary fields such as robotics, aerodynamics, and evolutionary biology. However, achieving this using a single…

Computer Vision and Pattern Recognition · Computer Science 2025-02-10 Zihao Zou , Ziyuan Qu , Xi Peng , Vivek Boominathan , Adithya Pediredla , Praneeth Chakravarthula

Over the past year, 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However, it can require a substantial amount of storage since each splat's…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Brent Zoomers , Maarten Wijnants , Ivan Molenaers , Joni Vanherck , Jeroen Put , Lode Jorissen , Nick Michiels

3D Gaussian Splatting (3DGS) enables high-fidelity real-time rendering, a key requirement for immersive applications. However, the extension of 3DGS to dynamic scenes remains limitations on the substantial data volume of dense Gaussians and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Jiayu Yang , Weijian Su , Songqian Zhang , Yuqi Han , Jinli Suo , Qiang Zhang

The advancement of real-time 3D scene reconstruction and novel view synthesis has been significantly propelled by 3D Gaussian Splatting (3DGS). However, effectively training large-scale 3DGS and rendering it in real-time across various…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yang Liu , He Guan , Chuanchen Luo , Lue Fan , Naiyan Wang , Junran Peng , Zhaoxiang Zhang