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Reconstructing dynamic driving scenes is essential for developing autonomous systems through sensor-realistic simulation. Although recent methods achieve high-fidelity reconstructions, they either rely on costly human annotations for object…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Carl Lindström , Mahan Rafidashti , Maryam Fatemi , Lars Hammarstrand , Martin R. Oswald , Lennart Svensson

Feed-forward 3D reconstruction offers substantial runtime advantages over per-scene optimization, which remains slow at inference and often fragile under sparse views. However, existing feed-forward methods still have potential for further…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Tianyu Chen , Wei Xiang , Kang Han , Yu Lu , Di Wu , Gaowen Liu , Ramana Rao Kompella

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

Persistent dynamic scene modeling for tracking and novel-view synthesis remains challenging due to the difficulty of capturing accurate deformations while maintaining computational efficiency. We propose SCas4D, a cascaded optimization…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Jipeng Lyu , Jiahua Dong , Yu-Xiong Wang

Fast and flexible 3D scene reconstruction from unstructured image collections remains a significant challenge. We present YoNoSplat, a feedforward model that reconstructs high-quality 3D Gaussian Splatting representations from an arbitrary…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Botao Ye , Boqi Chen , Haofei Xu , Daniel Barath , Marc Pollefeys

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

Novel view synthesis techniques predominantly utilize RGB cameras, inheriting their limitations such as the need for sufficient lighting, susceptibility to motion blur, and restricted dynamic range. In contrast, event cameras are…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Sohaib Zahid , Viktor Rudnev , Eddy Ilg , Vladislav Golyanik

3D Gaussian Splatting (3DGS) has shown remarkable success in synthesizing novel views given multiple views of a static scene. Yet, 3DGS faces challenges when applied to dynamic scenes because 3D Gaussian parameters need to be updated per…

Graphics · Computer Science 2024-07-08 Kai Katsumata , Duc Minh Vo , Hideki Nakayama

We introduce MVSplat, an efficient model that, given sparse multi-view images as input, predicts clean feed-forward 3D Gaussians. To accurately localize the Gaussian centers, we build a cost volume representation via plane sweeping, where…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Yuedong Chen , Haofei Xu , Chuanxia Zheng , Bohan Zhuang , Marc Pollefeys , Andreas Geiger , Tat-Jen Cham , Jianfei Cai

Recent advancements in 3D Gaussian Splatting (3D-GS) have demonstrated the potential of using 3D Gaussian primitives for high-speed, high-fidelity, and cost-efficient novel view synthesis from continuously calibrated input views. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Jingqian Wu , Shuo Zhu , Chutian Wang , Boxin Shi , Edmund Y. Lam

Recent advances in 3D Gaussian Splatting have enabled impressive photorealistic novel view synthesis. However, to transition from a pure rendering engine to a reliable spatial map for autonomous agents and safety-critical applications,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Chamuditha Jayanga Galappaththige , Thomas Gottwald , Peter Stehr , Edgar Heinert , Niko Suenderhauf , Dimity Miller , Matthias Rottmann

3D Gaussians have recently emerged as an effective scene representation for real-time splatting and accurate novel-view synthesis, motivating several works to adapt multi-view structure prediction networks to regress per-pixel 3D Gaussians…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Mehdi Hosseinzadeh , Shin-Fang Chng , Yi Xu , Simon Lucey , Ian Reid , Ravi Garg

The field of novel-view synthesis has recently witnessed the emergence of 3D Gaussian Splatting, which represents scenes in a point-based manner and renders through rasterization. This methodology, in contrast to Radiance Fields that rely…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Fengyi Zhang , Yadan Luo , Tianjun Zhang , Lin Zhang , Zi Huang

4D Gaussian Splatting (4DGS) has recently emerged as a promising technique for capturing complex dynamic 3D scenes with high fidelity. It utilizes a 4D Gaussian representation and a GPU-friendly rasterizer, enabling rapid rendering speeds.…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Xinjie Zhang , Zhening Liu , Yifan Zhang , Xingtong Ge , Dailan He , Tongda Xu , Yan Wang , Zehong Lin , Shuicheng Yan , Jun Zhang

Reconstructing dynamic scenes from video sequences is a highly promising task in the multimedia domain. While previous methods have made progress, they often struggle with slow rendering and managing temporal complexities such as…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Jinbo Yan , Rui Peng , Luyang Tang , Ronggang Wang

Surgical simulation is essential for medical training, enabling practitioners to develop crucial skills in a risk-free environment while improving patient safety and surgical outcomes. However, conventional methods for building simulation…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Zhenya Yang

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

High-fidelity 3D video reconstruction is essential for enabling real-time rendering of dynamic scenes with realistic motion in virtual and augmented reality (VR/AR). The deformation field paradigm of 3D Gaussian splatting has achieved…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Zhenyang Li , Xiaoyang Bai , Tongchen Zhang , Pengfei Shen , Weiwei Xu , Yifan Peng

Dynamic scene reconstruction is essential in robotic minimally invasive surgery, providing crucial spatial information that enhances surgical precision and outcomes. However, existing methods struggle to address the complex, temporally…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Fengze Li , Jishuai He , Jieming Ma , Zhijing Wu

The advent of 3D Gaussian Splatting (3D-GS) techniques and their dynamic scene modeling variants, 4D-GS, offers promising prospects for real-time rendering of dynamic surgical scenarios. However, the prerequisite for modeling dynamic scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Hengyu Liu , Yifan Liu , Chenxin Li , Wuyang Li , Yixuan Yuan
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