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3D Gaussian representations have emerged as a powerful paradigm for digital head modeling, achieving photorealistic quality with real-time rendering. However, intuitive and interactive creation or editing of 3D Gaussian head models remains…

Graphics · Computer Science 2026-04-22 Bo Li , Jiahao Kang , Yubo Ma , Feng-Lin Liu , Bin Liu , Fang-Lue Zhang , Lin Gao

Recent advances in 3D Gaussian Splatting (3D-GS) have shown remarkable success in representing 3D scenes and generating high-quality, novel views in real-time. However, 3D-GS and its variants assume that input images are captured based on…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Liao Shen , Tianqi Liu , Huiqiang Sun , Jiaqi Li , Zhiguo Cao , Wei Li , Chen Change Loy

Gaussian Splatting (GS) is a novel, state-of-the-art technique for rendering points in a 3D scene by approximating their contribution to image pixels through Gaussian distributions, warranting fast training and real-time rendering. The main…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Joanna Waczyńska , Piotr Borycki , Sławomir Tadeja , Jacek Tabor , Przemysław Spurek

Dynamic reconstruction of deformable tissues in endoscopic video is a key technology for robot-assisted surgery. Recent reconstruction methods based on neural radiance fields (NeRFs) have achieved remarkable results in the reconstruction of…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Weixing Xie , Junfeng Yao , Xianpeng Cao , Qiqin Lin , Zerui Tang , Xiao Dong , Xiaohu Guo

3D editing plays a crucial role in many areas such as gaming and virtual reality. Traditional 3D editing methods, which rely on representations like meshes and point clouds, often fall short in realistically depicting complex scenes. On the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Yiwen Chen , Zilong Chen , Chi Zhang , Feng Wang , Xiaofeng Yang , Yikai Wang , Zhongang Cai , Lei Yang , Huaping Liu , Guosheng Lin

Generalizable 3D Gaussian Splatting reconstruction showcases advanced Image-to-3D content creation but requires substantial computational resources and large datasets, posing challenges to training models from scratch. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Xiufeng Huang , Ka Chun Cheung , Runmin Cong , Simon See , Renjie Wan

3D Gaussian Splatting (3DGS) is a highly deployable real-time method for novel view synthesis. In practice, it requires a universal, consistent control mechanism that adjusts the trade-off between rendering quality and model compression…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Fengdi Zhang , Yibao Sun , Hongkun Cao , Ruqi Huang

3D Gaussian Splatting (3DGS) has emerged as a prominent technique with the potential to become a mainstream method for 3D representations. It can effectively transform multi-view images into explicit 3D Gaussian through efficient training,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Yanqi Bao , Tianyu Ding , Jing Huo , Yaoli Liu , Yuxin Li , Wenbin Li , Yang Gao , Jiebo Luo

3D Gaussian splatting (3DGS) has recently emerged as an alternative representation that leverages a 3D Gaussian-based representation and introduces an approximated volumetric rendering, achieving very fast rendering speed and promising…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Joo Chan Lee , Daniel Rho , Xiangyu Sun , Jong Hwan Ko , Eunbyung Park

We present a novel framework for enhancing the visual fidelity and consistency of text-guided 3D Gaussian Splatting (3DGS) editing. Existing editing approaches face two critical challenges: inconsistent geometric reconstructions across…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Xuanqi Zhang , Jieun Lee , Chris Joslin , Wonsook Lee

Since its introduction, 3D Gaussian Splatting (3DGS) has rapidly transformed the landscape of 3D scene representations, inspiring an extensive body of associated research. Follow-up work includes analyses and contributions that enhance the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Bernhard Kerbl

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

Rendering novel view images in dynamic scenes is a crucial yet challenging task. Current methods mainly utilize NeRF-based methods to represent the static scene and an additional time-variant MLP to model scene deformations, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Diwen Wan , Ruijie Lu , Gang Zeng

Image-based 3D reconstruction is a challenging task that involves inferring the 3D shape of an object or scene from a set of input images. Learning-based methods have gained attention for their ability to directly estimate 3D shapes. This…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Anurag Dalal , Daniel Hagen , Kjell G. Robbersmyr , Kristian Muri Knausgård

Over the past years, we have observed an abundance of approaches for modeling dynamic 3D scenes using Gaussian Splatting (GS). Such solutions use GS to represent the scene's structure and the neural network to model dynamics. Such…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Joanna Waczyńska , Piotr Borycki , Joanna Kaleta , Sławomir Tadeja , Przemysław Spurek

3D Gaussian Splatting (3DGS) has emerged as a powerful explicit representation enabling real-time, high-fidelity 3D reconstruction and novel view synthesis. However, its practical use is hindered by the massive memory and computational…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Seokhyun Youn , Soohyun Lee , Geonho Kim , Weeyoung Kwon , Sung-Ho Bae , Jihyong Oh

While 3D Gaussian Splatting (3DGS) excels in static scene modeling, its extension to dynamic scenes introduces significant challenges. Existing dynamic 3DGS methods suffer from either over-smoothing due to low-rank decomposition or feature…

Graphics · Computer Science 2025-08-08 Yifan Zhou , Beizhen Zhao , Pengcheng Wu , Hao Wang

Recent advancements in 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have achieved impressive results in real-time 3D reconstruction and novel view synthesis. However, these methods struggle in large-scale, unconstrained…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Niluthpol Chowdhury Mithun , Tuan Pham , Qiao Wang , Ben Southall , Kshitij Minhas , Bogdan Matei , Stephan Mandt , Supun Samarasekera , Rakesh Kumar

Scene image editing is crucial for entertainment, photography, and advertising design. Existing methods solely focus on either 2D individual object or 3D global scene editing. This results in a lack of a unified approach to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Qihang Zhang , Yinghao Xu , Chaoyang Wang , Hsin-Ying Lee , Gordon Wetzstein , Bolei Zhou , Ceyuan Yang

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…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Dingxi Zhang , Yu-Jie Yuan , Zhuoxun Chen , Fang-Lue Zhang , Zhenliang He , Shiguang Shan , Lin Gao