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We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xingjun Wang , Lianlei Shan

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

3D Gaussian Splatting (3DGS) has become an emerging tool for dynamic scene reconstruction. However, existing methods focus mainly on extending static 3DGS into a time-variant representation, while overlooking the rich motion information…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Zhiyang Guo , Wengang Zhou , Li Li , Min Wang , Houqiang Li

The recent advancements in 3D Gaussian splatting (3D-GS) have not only facilitated real-time rendering through modern GPU rasterization pipelines but have also attained state-of-the-art rendering quality. Nevertheless, despite its…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Ziyi Yang , Xinyu Gao , Yangtian Sun , Yihua Huang , Xiaoyang Lyu , Wen Zhou , Shaohui Jiao , Xiaojuan Qi , Xiaogang Jin

Pose-free feed-forward 3D Gaussian Splatting (3DGS) has opened a new frontier for rapid 3D modeling, enabling high-quality Gaussian representations to be generated from uncalibrated multi-view images in a single forward pass. The dominant…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Hwasik Jeong , Seungryong Lee , Gyeongjin Kang , Seungkwon Yang , Xiangyu Sun , Seungtae Nam , Eunbyung Park

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

Multi-subject customization aims to synthesize multiple user-specified subjects into a coherent image. To address issues such as subjects missing or conflicts, recent works incorporate layout guidance to provide explicit spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Binhe Yu , Zhen Wang , Kexin Li , Yuqian Yuan , Wenqiao Zhang , Long Chen , Juncheng Li , Jun Xiao , Yueting Zhuang

Modeling open-vocabulary language fields in 3D is essential for intuitive human-AI interaction and querying within physical environments. State-of-the-art approaches, such as LangSplat, leverage 3D Gaussian Splatting to efficiently…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Pranav Saxena

We introduce OceanSplat, a novel 3D Gaussian Splatting-based approach for high-fidelity underwater scene reconstruction. To overcome multi-view inconsistencies caused by scattering media, we design a trinocular setup for each camera pose by…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Minseong Kweon , Jinsun Park

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

Novel view synthesis of urban scenes is essential for autonomous driving-related applications.Existing NeRF and 3DGS-based methods show promising results in achieving photorealistic renderings but require slow, per-scene optimization. We…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Sheng Miao , Jiaxin Huang , Dongfeng Bai , Xu Yan , Hongyu Zhou , Yue Wang , Bingbing Liu , Andreas Geiger , Yiyi Liao

3D scene reconstruction is fundamental for spatial intelligence applications such as AR, robotics, and digital twins. Traditional multi-view stereo struggles with sparse viewpoints or low-texture regions, while neural rendering approaches,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Jiaqi Yao , Zhongmiao Yan , Jingyi Xu , Songpengcheng Xia , Yan Xiang , Ling Pei

This paper presents GaussEdit, a framework for adaptive 3D scene editing guided by text and image prompts. GaussEdit leverages 3D Gaussian Splatting as its backbone for scene representation, enabling convenient Region of Interest selection…

Graphics · Computer Science 2025-10-01 Zhenyu Shu , Junlong Yu , Kai Chao , Shiqing Xin , Ligang Liu

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

With 3D Gaussian Splatting (3DGS) advancing real-time and high-fidelity rendering for novel view synthesis, storage requirements pose challenges for their widespread adoption. Although various compression techniques have been proposed,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Yihang Chen , Qianyi Wu , Mengyao Li , Weiyao Lin , Mehrtash Harandi , Jianfei Cai

Gaussian splatting has recently gained traction as a compelling map representation for SLAM systems, enabling dense and photo-realistic scene modeling. However, its application to monocular SLAM remains challenging due to the lack of…

Robotics · Computer Science 2026-04-20 Dong-Uk Seo , Jinwoo Jeon , Eungchang Mason Lee , Hyun Myung

While neural 3D reconstruction has advanced substantially, its performance significantly degrades with sparse-view data, which limits its broader applicability, since SfM is often unreliable in sparse-view scenarios where feature matches…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Zhiwen Fan , Wenyan Cong , Kairun Wen , Kevin Wang , Jian Zhang , Xinghao Ding , Danfei Xu , Boris Ivanovic , Marco Pavone , Georgios Pavlakos , Zhangyang Wang , Yue Wang

Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Xinyu Gao , Wen Zhou , Shaohui Jiao , Yuqing Zhang , Xiaogang Jin

Recent feed-forward 3D gaussian splatting methods have made dramatic progress on individual aspects of 3D scene reconstruction, but no existing method jointly addresses dynamic content, multi-view input, and unknown camera poses in a single…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Matteo Balice , Yanik Kunzi , Chenyangguang Zhang , Matteo Matteucci , Marc Pollefeys , Sungwhan Hong

Exploring real-world spaces using novel-view synthesis is fun, and reimagining those worlds in a different style adds another layer of excitement. Stylized worlds can also be used for downstream tasks where there is limited training data…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Jamie Wynn , Zawar Qureshi , Jakub Powierza , Jamie Watson , Mohamed Sayed
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