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In low-light conditions, capturing videos with frame-based cameras often requires long exposure times, resulting in motion blur and reduced visibility. While frame-based motion deblurring and low-light enhancement have been studied, they…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Taewoo Kim , Jaeseok Jeong , Hoonhee Cho , Yuhwan Jeong , Kuk-Jin Yoon

Achieving robust and precise pose estimation in dynamic scenes is a significant research challenge in Visual Simultaneous Localization and Mapping (SLAM). Recent advancements integrating Gaussian Splatting into SLAM systems have proven…

Robotics · Computer Science 2024-11-14 Yueming Xu , Haochen Jiang , Zhongyang Xiao , Jianfeng Feng , Li Zhang

3D Gaussian Splatting has recently shown promising results as an alternative scene representation in SLAM systems to neural implicit representations. However, current methods either lack dense depth maps to supervise the mapping process or…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 F. Aykut Sarikamis , A. Aydin Alatan

Recent text-guided generation of individual 3D object has achieved great success using diffusion priors. However, these methods are not suitable for object insertion and replacement tasks as they do not consider the background, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-25 Hanyuan Xiao , Yingshu Chen , Huajian Huang , Haolin Xiong , Jing Yang , Pratusha Prasad , Yajie Zhao

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for real-time, high-resolution novel view synthesis. By representing scenes as a mixture of Gaussian primitives, 3DGS leverages GPU rasterization pipelines for efficient…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Peihao Wang , Yuehao Wang , Dilin Wang , Sreyas Mohan , Zhiwen Fan , Lemeng Wu , Ruisi Cai , Yu-Ying Yeh , Zhangyang Wang , Qiang Liu , Rakesh Ranjan

3D Gaussian Splatting (3DGS) leverages densely distributed Gaussian primitives for high-quality scene representation and reconstruction. While existing 3DGS methods perform well in scenes with minor view variation, large view changes from…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Chenhao Zhang , Yuanping Cao , Lei Zhang

Generalizable 3D Gaussian Splatting reconstruction showcases advanced Image-to-3D content creation but requires substantial computational resources and large datasets, posing challenges to training models from scratch. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Xiufeng Huang , Ka Chun Cheung , Runmin Cong , Simon See , Renjie Wan

We introduce GeoGS3D, a novel two-stage framework for reconstructing detailed 3D objects from single-view images. Inspired by the success of pre-trained 2D diffusion models, our method incorporates an orthogonal plane decomposition…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Qijun Feng , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang

Recent 3D Gaussian Splatting (3DGS) representations have demonstrated remarkable performance in novel view synthesis; further, material-lighting disentanglement on 3DGS warrants relighting capabilities and its adaptability to broader…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Kai Ye , Chong Gao , Guanbin Li , Wenzheng Chen , Baoquan Chen

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

In the field of 3D dynamic scene reconstruction, how to balance model convergence rate and rendering quality has long been a critical challenge that urgently needs to be addressed, particularly in high-precision modeling of scenes with…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Nengbo Lu , Minghua Pan , Shaohua Sun , Yizhou Liang

Jointly estimating camera poses and mapping scenes from RGBD images is a fundamental task in simultaneous localization and mapping (SLAM). State-of-the-art methods employ 3D Gaussians to represent a scene, and render these Gaussians through…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Pengchong Hu , Zhizhong Han

Efficient scene representations are essential for many real-world applications, especially those involving spatial measurement. Although current NeRF-based methods have achieved impressive results in reconstructing building-scale scenes,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Jianlin Guo , Haihong Xiao , Wenxiong Kang

3D Gaussian Splatting (3DGS) has emerged as a promising approach for CT reconstruction. However, existing methods rely on the average gradient magnitude of points within the view, often leading to severe needle-like artifacts under…

Image and Video Processing · Electrical Eng. & Systems 2025-08-07 Yikuang Yuluo , Yue Ma , Kuan Shen , Tongtong Jin , Wang Liao , Yangpu Ma , Fuquan Wang

3D Gaussian Splatting (3DGS) has attracted significant attention for its high-quality novel view rendering, inspiring research to address real-world challenges. While conventional methods depend on sharp images for accurate scene…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Jungho Lee , Suhwan Cho , Taeoh Kim , Ho-Deok Jang , Minhyeok Lee , Geonho Cha , Dongyoon Wee , Dogyoon Lee , Sangyoun Lee

Recent advances in 3D Gaussian Splatting (3DGS) have focused on accelerating optimization while preserving reconstruction quality. However, many proposed methods entangle implementation-level improvements with fundamental algorithmic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Florian Hahlbohm , Linus Franke , Martin Eisemann , Marcus Magnor

Due to the extremely low latency, events have been recently exploited to supplement lost information for motion deblurring. Existing approaches largely rely on the perfect pixel-wise alignment between intensity images and events, which is…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Mingyuan Lin , Chi Zhang , Chu He , Lei Yu

Recent advances in 3D Gaussian Splatting (3DGS) have enabled real-time, photorealistic scene reconstruction. However, conventional 3DGS frameworks typically rely on sparse point clouds derived from Structure-from-Motion (SfM), which…

Graphics · Computer Science 2026-03-25 Yan Fang , Jianfei Ge , Jiangjian Xiao

Event cameras are bio-inspired sensors that offer advantages over traditional cameras. They operate asynchronously, sampling the scene at microsecond resolution and producing a stream of brightness changes. This unconventional output has…

Computer Vision and Pattern Recognition · Computer Science 2022-09-14 Suman Ghosh , Guillermo Gallego

3D Gaussian Splatting (3DGS) effectively synthesizes novel views through its flexible representation, yet fails to accurately reconstruct scene geometry. While modern variants like PGSR introduce additional losses to ensure proper depth and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Zhentao Huang , Di Wu , Zhenbang He , Minglun Gong
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