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Related papers: OnlineSplatter: Pose-Free Online 3D Reconstruction…

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Sparse-view reconstruction models typically require precise camera poses, yet obtaining these parameters from sparse-view images remains challenging. We introduce FreeSplatter, a scalable feed-forward framework that generates high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Jiale Xu , Shenghua Gao , Ying Shan

We introduce the \method, an ultra-efficient approach for monocular 3D object reconstruction. Splatter Image is based on Gaussian Splatting, which allows fast and high-quality reconstruction of 3D scenes from multiple images. We apply…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Stanislaw Szymanowicz , Christian Rupprecht , Andrea Vedaldi

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

3D Gaussian Splatting achieves high-fidelity novel view synthesis, but its application to online long-sequence scenarios is still limited. Existing methods either rely on slow per-scene optimization or fail to provide efficient incremental…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Guichen Huang , Ruoyu Wang , Xiangjun Gao , Che Sun , Yuwei Wu , Shenghua Gao , Yunde Jia

High-quality scene reconstruction and novel view synthesis based on Gaussian Splatting (3DGS) typically require steady, high-quality photographs, often impractical to capture with handheld cameras. We present a method that adapts to camera…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Otto Seiskari , Jerry Ylilammi , Valtteri Kaatrasalo , Pekka Rantalankila , Matias Turkulainen , Juho Kannala , Esa Rahtu , Arno Solin

3D Gaussian Splatting (3DGS) is a promising technique for 3D reconstruction, offering efficient training and rendering speeds, making it suitable for real-time applications.However, current methods require highly controlled environments (no…

Computer Vision and Pattern Recognition · Computer Science 2024-07-31 Sara Sabour , Lily Goli , George Kopanas , Mark Matthews , Dmitry Lagun , Leonidas Guibas , Alec Jacobson , David J. Fleet , Andrea Tagliasacchi

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

While novel view synthesis for dynamic scenes has made significant progress, capturing skeleton models of objects and re-posing them remains a challenging task. To tackle this problem, in this paper, we propose a novel approach to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Diwen Wan , Yuxiang Wang , Ruijie Lu , Gang Zeng

We propose SelfSplat, a novel 3D Gaussian Splatting model designed to perform pose-free and 3D prior-free generalizable 3D reconstruction from unposed multi-view images. These settings are inherently ill-posed due to the lack of…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Gyeongjin Kang , Jisang Yoo , Jihyeon Park , Seungtae Nam , Hyeonsoo Im , Sangheon Shin , Sangpil Kim , Eunbyung Park

We present the first application of 3D Gaussian Splatting in monocular SLAM, the most fundamental but the hardest setup for Visual SLAM. Our method, which runs live at 3fps, utilises Gaussians as the only 3D representation, unifying the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Hidenobu Matsuki , Riku Murai , Paul H. J. Kelly , Andrew J. Davison

Transient objects in video sequences can significantly degrade the quality of 3D scene reconstructions. To address this challenge, we propose T-3DGS, a novel framework that robustly filters out transient distractors during 3D reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Alexander Markin , Vadim Pryadilshchikov , Artem Komarichev , Ruslan Rakhimov , Peter Wonka , Evgeny Burnaev

Articulated objects are ubiquitous in daily environments, and their 3D reconstruction holds great significance across various fields. However, existing articulated object reconstruction methods typically require costly inputs such as…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Di Wu , Liu Liu , Xueyu Yuan , Wenxiao Chen , Lijun Yue , Liuzhu Chen , Yiming Tang , Meng Wang

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

Recent advances in generalizable 3D Gaussian Splatting (3DGS) have enabled rapid 3D scene reconstruction within seconds, eliminating the need for per-scene optimization. However, existing methods primarily follow an offline reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Chong Xia , Fangfu Liu , Yule Wang , Yize Pang , Yueqi Duan

3D Gaussian Splatting (3DGS) has emerged as a high-fidelity and efficient paradigm for online free-viewpoint video (FVV) reconstruction, offering viewers rapid responsiveness and immersive experiences. However, existing online methods face…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Jiacong Chen , Qingyu Mao , Youneng Bao , Xiandong Meng , Fanyang Meng , Ronggang Wang , Yongsheng Liang

Real-time reconstruction of dynamic 3D scenes from uncalibrated video streams demands robust online methods that recover scene dynamics from sparse observations under strict latency and memory constraints. Yet most dynamic reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Zike Wu , Qi Yan , Xuanyu Yi , Lele Wang , Renjie Liao

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

Recently, the integration of the efficient feed-forward scheme into 3D Gaussian Splatting (3DGS) has been actively explored. However, most existing methods focus on sparse view reconstruction of small regions and cannot produce eligible…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Yunsong Wang , Tianxin Huang , Hanlin Chen , Gim Hee Lee

Recent advancements in 3D Gaussian Splatting (3DGS) have demonstrated its potential for efficient and photorealistic 3D reconstructions, which is crucial for diverse applications such as robotics and immersive media. However, current…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Daheng Yin , Isaac Ding , Yili Jin , Jianxin Shi , Jiangchuan Liu

We propose an approach for reconstructing free-moving object from a monocular RGB video. Most existing methods either assume scene prior, hand pose prior, object category pose prior, or rely on local optimization with multiple sequence…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Haixin Shi , Yinlin Hu , Daniel Koguciuk , Juan-Ting Lin , Mathieu Salzmann , David Ferstl
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