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Representing and rendering dynamic scenes has been an important but challenging task. Especially, to accurately model complex motions, high efficiency is usually hard to guarantee. To achieve real-time dynamic scene rendering while also…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Guanjun Wu , Taoran Yi , Jiemin Fang , Lingxi Xie , Xiaopeng Zhang , Wei Wei , Wenyu Liu , Qi Tian , Xinggang Wang

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

Recent advances in 3D Gaussian Splatting have shown promising results. Existing methods typically assume static scenes and/or multiple images with prior poses. Dynamics, sparse views, and unknown poses significantly increase the problem…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Weihang Li , Weirong Chen , Shenhan Qian , Jiajie Chen , Daniel Cremers , Haoang Li

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

3D Gaussian Splatting has shown fast and high-quality rendering results in static scenes by leveraging dense 3D prior and explicit representations. Unfortunately, the benefits of the prior and representation do not involve novel view…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Junoh Lee , Chang-Yeon Won , Hyunjun Jung , Inhwan Bae , Hae-Gon Jeon

Simultaneous localization and mapping (SLAM) technology has recently achieved photorealistic mapping capabilities thanks to the real-time, high-fidelity rendering enabled by 3D Gaussian Splatting (3DGS). However, due to the static…

Robotics · Computer Science 2025-12-01 Zhicong Sun , Jacqueline Lo , Jinxing Hu

While dynamic novel view synthesis from 2D videos has seen progress, achieving efficient reconstruction and rendering of dynamic scenes remains a challenging task. In this paper, we introduce Disentangled 4D Gaussian Splatting…

Graphics · Computer Science 2025-10-31 Hao Feng , Hao Sun , Wei Xie , Zhi Zuo , Zhengzhe Liu

Efficient and accurate object pose estimation is an essential component for modern vision systems in many applications such as Augmented Reality, autonomous driving, and robotics. While research in model-based 6D object pose estimation has…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Yufeng Jin , Vignesh Prasad , Snehal Jauhri , Mathias Franzius , Georgia Chalvatzaki

LongSplat addresses critical challenges in novel view synthesis (NVS) from casually captured long videos characterized by irregular camera motion, unknown camera poses, and expansive scenes. Current methods often suffer from pose drift,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Chin-Yang Lin , Cheng Sun , Fu-En Yang , Min-Hung Chen , Yen-Yu Lin , Yu-Lun Liu

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

We present GP-4DGS, a novel framework that integrates Gaussian Processes (GPs) into 4D Gaussian Splatting (4DGS) for principled probabilistic modeling of dynamic scenes. While existing 4DGS methods focus on deterministic reconstruction,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Mijeong Kim , Jungtaek Kim , Bohyung Han

Deformable 3D Gaussian Splatting (3D-GS) is limited by missing intermediate motion information due to the low temporal resolution of RGB cameras. To address this, we introduce the first approach combining event cameras, which capture…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Wenhao Xu , Wenming Weng , Yueyi Zhang , Ruikang Xu , Zhiwei Xiong

The availability of large-scale multimodal datasets and advancements in diffusion models have significantly accelerated progress in 4D content generation. Most prior approaches rely on multiple image or video diffusion models, utilizing…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Hanwen Liang , Yuyang Yin , Dejia Xu , Hanxue Liang , Zhangyang Wang , Konstantinos N. Plataniotis , Yao Zhao , Yunchao Wei

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

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

Advances in generative modeling have significantly enhanced digital content creation, extending from 2D images to complex 3D and 4D scenes. Despite substantial progress, producing high-fidelity and temporally consistent dynamic 4D content…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 DongFu Yin , Xiaotian Chen , Fei Richard Yu , Xuanchen Li , Xinhao Zhang

This paper introduces GS-Pose, a unified framework for localizing and estimating the 6D pose of novel objects. GS-Pose begins with a set of posed RGB images of a previously unseen object and builds three distinct representations stored in a…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Dingding Cai , Janne Heikkilä , Esa Rahtu

Realistic reconstruction of dynamic 4D scenes from monocular videos is essential for understanding the physical world. Despite recent progress in neural rendering, existing methods often struggle to recover accurate 3D geometry and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Haoran Zhou , Gim Hee Lee

3D Gaussian Splatting has recently emerged as a powerful tool for fast and accurate novel-view synthesis from a set of posed input images. However, like most novel-view synthesis approaches, it relies on accurate camera pose information,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Christian Schmidt , Jens Piekenbrinck , Bastian Leibe

Existing 4D Gaussian Splatting (4DGS) methods struggle to accurately reconstruct dynamic scenes, often failing to resolve ambiguous pixel correspondences and inadequate densification in dynamic regions. We address these issues by…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Taeho Kang , Jaeyeon Park , Kyungjin Lee , Youngki Lee