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Recent advances in driving-scene generation and reconstruction have demonstrated significant potential for enhancing autonomous driving systems by producing scalable and controllable training data. Existing generation methods primarily…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Ziyue Zhu , Zhanqian Wu , Zhenxin Zhu , Lijun Zhou , Haiyang Sun , Bing Wan , Kun Ma , Guang Chen , Hangjun Ye , Jin Xie , jian Yang

Dynamic scene reconstruction represents a fundamental yet demanding challenge in computer vision and robotics. While recent progress in 3DGS-based methods has advanced dynamic scene modeling, obtaining high-fidelity rendering and accurate…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Yinan Deng , Jianyu Dou , Jiahui Wang , Jingyu Zhao , Yi Yang , Yufeng Yue

We introduce GaussianOcc, a systematic method that investigates the two usages of Gaussian splatting for fully self-supervised and efficient 3D occupancy estimation in surround views. First, traditional methods for self-supervised 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Wanshui Gan , Fang Liu , Hongbin Xu , Ningkai Mo , Naoto Yokoya

Novel view synthesis has been greatly enhanced by the development of radiance field methods. The introduction of 3D Gaussian Splatting (3DGS) has effectively addressed key challenges, such as long training times and slow rendering speeds,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Gopi Raju Matta , Reddypalli Trisha , Kaushik Mitra

Gaussian splatting has emerged as a powerful 3D representation that harnesses the advantages of both explicit (mesh) and implicit (NeRF) 3D representations. In this paper, we seek to leverage Gaussian splatting to generate realistic…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Ye Yuan , Xueting Li , Yangyi Huang , Shalini De Mello , Koki Nagano , Jan Kautz , Umar Iqbal

Recently, 3D Gaussian Splatting (3DGS) has emerged as an efficient approach for accurately representing scenes. However, despite its superior novel view synthesis capabilities, extracting the geometry of the scene directly from the Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Yaniv Wolf , Amit Bracha , Ron Kimmel

Photorealistic and controllable human avatars have gained popularity in the research community thanks to rapid advances in neural rendering, providing fast and realistic synthesis tools. However, a limitation of current solutions is the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Mohamed Ilyes Lakhal , Richard Bowden

3D Gaussian Splatting (3DGS) has emerged as a prominent 3D representation for high-fidelity and real-time rendering. Prior work has coupled physics simulation with Gaussians, but predominantly targets soft, deformable materials, leaving…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Bei Huang , Yixin Chen , Ruijie Lu , Gang Zeng , Hongbin Zha , Yuru Pei , Siyuan Huang

This paper presents RoGSplat, a novel approach for synthesizing high-fidelity novel views of unseen human from sparse multi-view images, while requiring no cumbersome per-subject optimization. Unlike previous methods that typically struggle…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Junjin Xiao , Qing Zhang , Yonewei Nie , Lei Zhu , Wei-Shi Zheng

Recent progress in feed-forward 3D Gaussian Splatting (3DGS) has notably improved rendering quality. However, the spatially uniform and highly redundant 3DGS map generated by previous feed-forward 3DGS methods limits their integration into…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Zicheng Zhang , Xiangting Meng , Ke Wu , Wenchao Ding

Gaussian Splatting (GS) is a recent and pivotal technique in 3D computer graphics. GS-based algorithms almost always bypass classical methods such as ray tracing, which offer numerous inherent advantages for rendering. For example, ray…

We present GaussianAvatar, an efficient approach to creating realistic human avatars with dynamic 3D appearances from a single video. We start by introducing animatable 3D Gaussians to explicitly represent humans in various poses and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Liangxiao Hu , Hongwen Zhang , Yuxiang Zhang , Boyao Zhou , Boning Liu , Shengping Zhang , Liqiang Nie

The recent Gaussian Splatting achieves high-quality and real-time novel-view synthesis of the 3D scenes. However, it is solely concentrated on the appearance and geometry modeling, while lacking in fine-grained object-level scene…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Mingqiao Ye , Martin Danelljan , Fisher Yu , Lei Ke

3D Gaussian Splatting (3DGS) achieves impressive quality and rendering speed, but with millions of 3D Gaussians and significant storage and transmission costs. In this paper, we aim to develop a simple yet effective method called NeuralGS…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Zhenyu Tang , Chaoran Feng , Xinhua Cheng , Wangbo Yu , Junwu Zhang , Yuan Liu , Xiaoxiao Long , Wenping Wang , Li Yuan

We leverage increasingly popular three-dimensional neural representations in order to construct a unified and consistent explanation of a collection of uncalibrated images of the human face. Our approach utilizes Gaussian Splatting, since…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Haodi He , Jihun Yu , Ronald Fedkiw

Level of Detail (LoD) is a fundamental technique in real-time computer graphics for managing the rendering costs of complex scenes while preserving visual fidelity. Traditionally, LoD is implemented using discrete levels (DLoD), where…

Graphics · Computer Science 2026-04-02 Zhigang Cheng , Mingchao Sun , Yu Liu , Zengye Ge , Luyang Tang , Mu Xu , Yangyan Li , Peng Pan

3D Gaussian Splatting has achieved impressive performance in novel view synthesis with real-time rendering capabilities. However, reconstructing high-quality surfaces with fine details using 3D Gaussians remains a challenging task. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Jiepeng Wang , Yuan Liu , Peng Wang , Cheng Lin , Junhui Hou , Xin Li , Taku Komura , Wenping Wang

Particle-based representations of radiance fields such as 3D Gaussian Splatting have found great success for reconstructing and re-rendering of complex scenes. Most existing methods render particles via rasterization, projecting them to…

3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis performance. While conventional methods require per-scene optimization, more recently several feed-forward methods have been proposed to generate pixel-aligned…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Shengjun Zhang , Xin Fei , Fangfu Liu , Haixu Song , Yueqi Duan

Recent advancements in Generalizable Gaussian Splatting have enabled robust 3D reconstruction from sparse input views by utilizing feed-forward Gaussian Splatting models, achieving superior cross-scene generalization. However, while many…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Zhicong Wu , Hongbin Xu , Gang Xu , Ping Nie , Zhixin Yan , Jinkai Zheng , Liangqiong Qu , Ming Li , Liqiang Nie
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