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3D Gaussian Splatting (3DGS) has emerged as a key rendering pipeline for digital asset creation due to its balance between efficiency and visual quality. To address the issues of unstable pose estimation and scene representation distortion…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Meijun Guo , Yongliang Shi , Caiyun Liu , Yixiao Feng , Ming Ma , Tinghai Yan , Weining Lu , Bin Liang

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 introduce Crowd-Sourced Splatting (CSS), a novel 3D Gaussian Splatting (3DGS) pipeline designed to overcome the challenges of pose-free scene reconstruction using crowd-sourced imagery. The dream of reconstructing historically…

Computer Vision and Pattern Recognition · Computer Science 2024-09-16 Runze Chen , Mingyu Xiao , Haiyong Luo , Fang Zhao , Fan Wu , Hao Xiong , Qi Liu , Meng Song

Gaussian splatting has emerged as a powerful tool for high-fidelity reconstruction of dynamic scenes. However, existing methods primarily rely on implicit motion representations, such as encoding motions into neural networks or per-Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Xinyu Zhang , Haonan Chang , Yuhan Liu , Abdeslam Boularias

Six degree of freedom (6DoF) pose estimation for novel objects is a critical task in computer vision, yet it faces significant challenges in high-speed and low-light scenarios where standard RGB cameras suffer from motion blur. While event…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Huiming Yang , Linglin Liao , Fei Ding , Sibo Wang , Zijian Zeng

Tracking the 6DoF pose of unknown objects in monocular RGB video sequences is crucial for robotic manipulation. However, existing approaches typically rely on accurate depth information, which is non-trivial to obtain in real-world…

Computer Vision and Pattern Recognition · Computer Science 2024-12-04 Zhiyuan Chen , Fan Lu , Guo Yu , Bin Li , Sanqing Qu , Yuan Huang , Changhong Fu , Guang Chen

Rendering complex reflection of real-world scenes using 3D Gaussian splatting has been a quite promising solution for photorealistic novel view synthesis, but still faces bottlenecks especially in rendering speed and memory storage. This…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Chang Liu , Hongliang Yuan , Lianghao Zhang , Sichao Wang , Jianwei Guo , Shi-Sheng Huang

Reconstructing 3D scenes from sparse, unposed images remains challenging under real-world conditions with varying illumination and transient occlusions. Existing methods rely on scene-specific optimization using appearance embeddings or…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Vinayak Gupta , Chih-Hao Lin , Shenlong Wang , Anand Bhattad , Jia-Bin Huang

We propose DrivingForward, a feed-forward Gaussian Splatting model that reconstructs driving scenes from flexible surround-view input. Driving scene images from vehicle-mounted cameras are typically sparse, with limited overlap, and the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Qijian Tian , Xin Tan , Yuan Xie , Lizhuang Ma

Reconstructing 3D scenes using 3D Gaussian Splatting (3DGS) from sparse views is an ill-posed problem due to insufficient information, often resulting in noticeable artifacts. While recent approaches have sought to leverage generative…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Xingyilang Yin , Qi Zhang , Jiahao Chang , Ying Feng , Qingnan Fan , Xi Yang , Chi-Man Pun , Huaqi Zhang , Xiaodong Cun

Reconstructing a dynamic target moving over a large area is challenging. Standard approaches for dynamic object reconstruction require dense coverage in both the viewing space and the temporal dimension, typically relying on multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Jun-Jee Chao , Volkan Isler

The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the rendering speed of novel view synthesis. Unlike neural implicit representations like Neural Radiance Fields (NeRF) that represent a 3D scene with position and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Tong Wu , Yu-Jie Yuan , Ling-Xiao Zhang , Jie Yang , Yan-Pei Cao , Ling-Qi Yan , Lin Gao

Sparse-view 3D Gaussian splatting seeks to render high-quality novel views of 3D scenes from a limited set of input images. While recent pose-free feed-forward methods leveraging pre-trained 3D priors have achieved impressive results, most…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Muyu Xu , Fangneng Zhan , Xiaoqin Zhang , Ling Shao , Shijian Lu

Recent advances in novel view synthesis (NVS) have enabled real-time rendering with 3D Gaussian Splatting (3DGS). However, existing methods struggle with artifacts and missing regions when rendering from viewpoints that deviate from the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Minsu Kim , Subin Jeon , In Cho , Mijin Yoo , Seon Joo Kim

In this paper, we introduce Splatt3R, a pose-free, feed-forward method for in-the-wild 3D reconstruction and novel view synthesis from stereo pairs. Given uncalibrated natural images, Splatt3R can predict 3D Gaussian Splats without…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Brandon Smart , Chuanxia Zheng , Iro Laina , Victor Adrian Prisacariu

Reconstructing static 3D scene from monocular video with dynamic objects is important for numerous applications such as virtual reality and autonomous driving. Current approaches typically rely on background for static scene reconstruction,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Yedong Shen , Shiqi Zhang , Sha Zhang , Yifan Duan , Xinran Zhang , Wenhao Yu , Lu Zhang , Jiajun Deng , Yanyong Zhang

Recent advances in 3D Gaussian Splatting (3DGS) have enabled efficient free-viewpoint rendering and photorealistic scene reconstruction. While on-the-fly extensions of 3DGS have shown promise for real-time reconstruction from monocular RGB…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Yijia Guo , Tong Hu , Zhiwei Li , Liwen Hu , Keming Qian , Xitong Lin , Shengbo Chen , Tiejun Huang , Lei Ma

We tackle the challenge of concurrent reconstruction at the part level with the RGB appearance and estimation of motion parameters for building digital twins of articulated objects using the 3D Gaussian Splatting (3D-GS) method. With two…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Junfu Guo , Yu Xin , Gaoyi Liu , Kai Xu , Ligang Liu , Ruizhen Hu

The efficient spatial allocation of primitives serves as the foundation of 3D Gaussian Splatting, as it directly dictates the synergy between representation compactness, reconstruction speed, and rendering fidelity. Previous solutions,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Roni Itkin , Noam Issachar , Yehonatan Keypur , Xingyu Chen , Anpei Chen , Sagie Benaim

Surface reconstruction has been widely studied in computer vision and graphics. However, existing surface reconstruction works struggle to recover accurate scene geometry when the input views are extremely sparse. To address this issue, we…

Graphics · Computer Science 2025-11-26 Hanzhi Chang , Ruijie Zhu , Wenjie Chang , Mulin Yu , Yanzhe Liang , Jiahao Lu , Zhuoyuan Li , Tianzhu Zhang