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Reconstructing dynamic 3D scenes from 2D images and generating diverse views over time is challenging due to scene complexity and temporal dynamics. Despite advancements in neural implicit models, limitations persist: (i) Inadequate Scene…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Zeyu Yang , Hongye Yang , Zijie Pan , Li Zhang

Dynamic scene rendering opens new avenues in autonomous driving by enabling closed-loop simulations with photorealistic data, which is crucial for validating end-to-end algorithms. However, the complex and highly dynamic nature of traffic…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Rui Song , Chenwei Liang , Yan Xia , Walter Zimmer , Hu Cao , Holger Caesar , Andreas Festag , Alois Knoll

Dynamic 4D Gaussian Splatting (4DGS) effectively extends the high-speed rendering capabilities of 3D Gaussian Splatting (3DGS) to represent volumetric videos. However, the large number of Gaussians, substantial temporal redundancies, and…

Graphics · Computer Science 2026-01-14 Hyeongmin Lee , Kyungjune Baek

In the realm of robot-assisted minimally invasive surgery, dynamic scene reconstruction can significantly enhance downstream tasks and improve surgical outcomes. Neural Radiance Fields (NeRF)-based methods have recently risen to prominence…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Yiming Huang , Beilei Cui , Long Bai , Ziqi Guo , Mengya Xu , Mobarakol Islam , Hongliang Ren

In this paper, we propose MoDGS, a new pipeline to render novel views of dy namic scenes from a casually captured monocular video. Previous monocular dynamic NeRF or Gaussian Splatting methods strongly rely on the rapid move ment of input…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Qingming Liu , Yuan Liu , Jiepeng Wang , Xianqiang Lyv , Peng Wang , Wenping Wang , Junhui Hou

Recent advances in 4D scene reconstruction have significantly improved dynamic modeling across various domains. However, existing approaches remain limited under aerial conditions with single-view capture, wide spatial range, and dynamic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Hanyang Liu , Rongjun Qin

Creating a photorealistic scene and human reconstruction from a single monocular in-the-wild video figures prominently in the perception of a human-centric 3D world. Recent neural rendering advances have enabled holistic human-scene…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Zetong Zhang , Manuel Kaufmann , Lixin Xue , Jie Song , Martin R. Oswald

Differentiable rendering techniques have recently shown promising results for free-viewpoint video synthesis of characters. However, such methods, either Gaussian Splatting or neural implicit rendering, typically necessitate per-subject…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Boyao Zhou , Shunyuan Zheng , Hanzhang Tu , Ruizhi Shao , Boning Liu , Shengping Zhang , Liqiang Nie , Yebin Liu

Reconstructing dynamic 3D scenes from monocular video has broad applications in AR/VR, robotics, and autonomous navigation, but often fails due to severe motion blur caused by camera and object motion. Existing methods commonly follow a…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Zhijing Wu , Longguang Wang

Recently, Gaussian splatting has received more and more attention in the field of static scene rendering. Due to the low computational overhead and inherent flexibility of explicit representations, plane-based explicit methods are popular…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Jiawei Xu , Zexin Fan , Jian Yang , Jin Xie

Using accurate depth priors in 3D Gaussian Splatting helps mitigate artifacts caused by sparse training data and textureless surfaces. However, acquiring accurate depth maps requires specialized acquisition systems. Foundation monocular…

Computer Vision and Pattern Recognition · Computer Science 2026-04-08 Wenhui Xiao , Ethan Goan , Rodrigo Santa Cruz , David Ahmedt-Aristizabal , Olivier Salvado , Clinton Fookes , Leo Lebrat

While 3D Gaussian Splatting (3DGS) enables high-quality, real-time rendering for bounded scenes, its extension to large-scale urban environments gives rise to critical challenges in terms of geometric consistency, memory efficiency, and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-23 Changbai Li , Haodong Zhu , Hanlin Chen , Xiuping Liang , Tongfei Chen , Shuwei Shao , Linlin Yang , Huobin Tan , Baochang Zhang

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

We have recently seen tremendous progress in photo-real human modeling and rendering. Yet, efficiently rendering realistic human performance and integrating it into the rasterization pipeline remains challenging. In this paper, we present…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Yuheng Jiang , Zhehao Shen , Penghao Wang , Zhuo Su , Yu Hong , Yingliang Zhang , Jingyi Yu , Lan Xu

We introduce ShapeGaussian, a high-fidelity, template-free method for 4D human reconstruction from casual monocular videos. Generic reconstruction methods lacking robust vision priors, such as 4DGS, struggle to capture high-deformation…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Zhenxiao Liang , Ning Zhang , Youbao Tang , Ruei-Sung Lin , Qixing Huang , Peng Chang , Jing Xiao

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

Simultaneous Localization and Mapping (SLAM) with 3D Gaussian Splatting (3DGS) enables fast, differentiable rendering and high-fidelity reconstruction across diverse real-world scenes. However, existing 3DGS-SLAM approaches handle…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Anh Thuan Tran , Jana Kosecka

Gaussian Splatting (GS) has significantly elevated scene reconstruction efficiency and novel view synthesis (NVS) accuracy compared to Neural Radiance Fields (NeRF), particularly for dynamic scenes. However, current 4D NVS methods, whether…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Fang Li , Hao Zhang , Narendra Ahuja

Reconstructing dynamic 4D scenes is an important yet challenging task. While 3D foundation models like VGGT excel in static settings, they often struggle with dynamic sequences where motion causes significant geometric ambiguity. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Ying Zang , Yidong Han , Chaotao Ding , Yuanqi Hu , Deyi Ji , Qi Zhu , Xuanfu Li , Jin Ma , Lingyun Sun , Tianrun Chen , Lanyun Zhu

Gaussian Splatting has been considered as a novel way for view synthesis of dynamic scenes, which shows great potential in AIoT applications such as digital twins. However, recent dynamic Gaussian Splatting methods significantly degrade…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Yiwei Li , Jiannong Cao , Penghui Ruan , Divya Saxena , Songye Zhu , Yinfeng Cao