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While generalizable 3D Gaussian splatting enables efficient, high-quality rendering of unseen scenes, it heavily depends on precise camera poses for accurate geometry. In real-world scenarios, obtaining accurate poses is challenging,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Youngju Na , Taeyeon Kim , Jumin Lee , Kyu Beom Han , Woo Jae Kim , Sung-eui Yoon

The field of 3D reconstruction from images has rapidly evolved in the past few years, first with the introduction of Neural Radiance Field (NeRF) and more recently with 3D Gaussian Splatting (3DGS). The latter provides a significant edge…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Avinash Paliwal , Wei Ye , Jinhui Xiong , Dmytro Kotovenko , Rakesh Ranjan , Vikas Chandra , Nima Khademi Kalantari

This paper presents the first photo-realistic LiDAR-Inertial-Camera Gaussian Splatting SLAM system that simultaneously addresses visual quality, geometric accuracy, and real-time performance. The proposed method performs robust and accurate…

Robotics · Computer Science 2025-07-10 Xiaolei Lang , Jiajun Lv , Kai Tang , Laijian Li , Jianxin Huang , Lina Liu , Yong Liu , Xingxing Zuo

Recent advances in 3D Gaussian Splatting (3DGS) present two main directions: feed-forward models offer fast inference in sparse-view settings, while per-scene optimization yields high-quality renderings but is computationally expensive. To…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Yueh-Cheng Liu , Jozef Hladký , Matthias Nießner , Angela Dai

We present an iterative framework to improve the amortized approximations of posterior distributions in the context of Bayesian inverse problems, which is inspired by loop-unrolled gradient descent methods and is theoretically grounded in…

Machine Learning · Computer Science 2023-05-16 Rafael Orozco , Ali Siahkoohi , Mathias Louboutin , Felix J. Herrmann

Feed-forward 3D Gaussian Splatting (3DGS) models enable real-time scene generation but are hindered by suboptimal pixel-aligned primitive placement, which relies on a dense, rigid grid that limits both quality and efficiency. We introduce a…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Arthur Moreau , Richard Shaw , Michal Nazarczuk , Jisu Shin , Thomas Tanay , Zhensong Zhang , Songcen Xu , Eduardo Pérez-Pellitero

Rendering 3D surfaces has been revolutionized within the modeling of radiance fields through either 3DGS or NeRF. Although 3DGS has shown advantages over NeRF in terms of rendering quality or speed, there is still room for improvement in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Takeshi Noda , Yu-Shen Liu , Zhizhong Han

Four-dimensional computed tomography (4D CT) reconstruction is crucial for capturing dynamic anatomical changes but faces inherent limitations from conventional phase-binning workflows. Current methods discretize temporal resolution into…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Weihao Yu , Yuanhao Cai , Ruyi Zha , Zhiwen Fan , Chenxin Li , Yixuan Yuan

Geometric priors are often used to enhance 3D reconstruction. With many smartphones featuring low-resolution depth sensors and the prevalence of off-the-shelf monocular geometry estimators, incorporating geometric priors as regularization…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Xuqian Ren , Matias Turkulainen , Jiepeng Wang , Otto Seiskari , Iaroslav Melekhov , Juho Kannala , Esa Rahtu

3D Gaussian Splatting (3DGS) enables high-fidelity real-time rendering, a key requirement for immersive applications. However, the extension of 3DGS to dynamic scenes remains limitations on the substantial data volume of dense Gaussians and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Jiayu Yang , Weijian Su , Songqian Zhang , Yuqi Han , Jinli Suo , Qiang Zhang

Feed-forward 3D Gaussian Splatting methods have achieved impressive reconstruction quality for autonomous driving scenes, yet they entangle scene geometry with transient appearance properties such as lighting, weather, and time of day. This…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Quentin Herau , Tianshuo Xu , Depu Meng , Jiezhi Yang , Chensheng Peng , Spencer Sherk , Yihan Hu , Wei Zhan

3D Gaussian Splatting reconstructs scenes by starting from a sparse Structure-from-Motion initialization and refining under-reconstructed regions. This process is slow, as it requires multiple densification steps where Gaussians are…

Graphics · Computer Science 2026-02-13 Dmytro Kotovenko , Olga Grebenkova , Björn Ommer

Recent advances in Gaussian Splatting have significantly boosted the reconstruction of head avatars, enabling high-quality facial modeling by representing an 3D avatar as a collection of 3D Gaussians. However, existing methods predominantly…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Shiqi Xin , Xiaolin Zhang , Yanbin Liu , Peng Zhang , Caifeng Shan

3D object generation from a single image involves estimating the full 3D geometry and texture of unseen views from an unposed RGB image captured in the wild. Accurately reconstructing an object's complete 3D structure and texture has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Hritam Basak , Hadi Tabatabaee , Shreekant Gayaka , Ming-Feng Li , Xin Yang , Cheng-Hao Kuo , Arnie Sen , Min Sun , Zhaozheng Yin

Three-dimensional Gaussian Splatting (3DGS) has recently emerged as an efficient representation for novel-view synthesis, achieving impressive visual quality. However, in scenes dominated by large and low-texture regions, common in indoor…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Xirui Jin , Renbiao Jin , Boying Li , Danping Zou , Wenxian Yu

Gaussian Splatting (GS) has gained attention as a fast and effective method for novel view synthesis. It has also been applied to 3D reconstruction using multi-view images and can achieve fast and accurate 3D reconstruction. However, GS…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Natsuki Takama , Shintaro Ito , Koichi Ito , Hwann-Tzong Chen , Takafumi Aoki

We present TokenSplat, a feed-forward framework for joint 3D Gaussian reconstruction and camera pose estimation from unposed multi-view images. At its core, TokenSplat introduces a Token-aligned Gaussian Prediction module that aligns…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Yihui Li , Chengxin Lv , Zichen Tang , Hongyu Yang , Di Huang

Recently, Gaussian Splatting (GS) has received a lot of attention in surface reconstruction. However, while 3D objects can be of complex and diverse shapes in the real world, existing GS-based methods only limitedly use a single type of…

Computer Vision and Pattern Recognition · Computer Science 2025-07-16 Haoxuan Qu , Yujun Cai , Hossein Rahmani , Ajay Kumar , Junsong Yuan , Jun Liu

Gaussian splatting, renowned for its exceptional rendering quality and efficiency, has emerged as a prominent technique in 3D scene representation. However, the substantial data volume of Gaussian splatting impedes its practical utility in…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Xiangrui Liu , Xinju Wu , Pingping Zhang , Shiqi Wang , Zhu Li , Sam Kwong

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