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3D Gaussian Splatting (3DGS) has emerged as a core technique for 3D representation. Its effectiveness largely depends on precise camera poses and accurate point cloud initialization, which are often derived from pretrained Multi-View Stereo…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Chong Cheng , Zijian Wang , Sicheng Yu , Yu Hu , Nanjie Yao , Hao Wang

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

When viewing a 3D Gaussian Splatting (3DGS) model from camera positions significantly outside the training data distribution, substantial visual noise commonly occurs. These artifacts result from the lack of training data in these…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Damian Bowness , Charalambos Poullis

Reconstructing high-resolution (HR) 3D Gaussian Splatting (3DGS) models from low-resolution (LR) inputs remains challenging due to the lack of fine-grained textures and geometry. Existing methods typically rely on pre-trained 2D…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Xiang Feng , Tieshi Zhong , Shuo Chang , Weiliu Wang , Chengkai Wang , Yifei Chen , Yuhe Wang , Zhenzhong Kuang , Xuefei Yin , Yanming Zhu

Sparse-view 3D reconstruction is a major challenge in computer vision, aiming to create complete three-dimensional models from limited viewing angles. Key obstacles include: 1) a small number of input images with inconsistent information;…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Bi'an Du , Lingbei Meng , Wei Hu

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

3D Gaussian Splatting (3DGS) achieves remarkable results in the field of surface reconstruction. However, when Gaussian normal vectors are aligned within the single-view projection plane, while the geometry appears reasonable in the current…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Bo Jia , Yanan Guo , Ying Chang , Benkui Zhang , Ying Xie , Kangning Du , Lin Cao

Recent advancements in 3D Gaussian Splatting (3DGS), which lead to high-quality novel view synthesis and accelerated rendering, have remarkably improved the quality of radiance field reconstruction. However, the extraction of mesh from a…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Shengchao Zhao , Yundong Li

3D Gaussian Splatting (3DGS) has recently emerged as a pioneering approach in explicit scene rendering and computer graphics. Unlike traditional neural radiance field (NeRF) methods, which typically rely on implicit, coordinate-based models…

Estimating metric relative camera pose from a pair of images is of great importance for 3D reconstruction and localisation. However, conventional two-view pose estimation methods are not metric, with camera translation known only up to a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Yumin Li , Dylan Campbell

Recent advancements in 3D Gaussian Splatting (3DGS) have greatly influenced neural fields, as it enables high-fidelity rendering with impressive visual quality. However, 3DGS has difficulty accurately representing surfaces. In contrast,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Haofan Ren , Qingsong Yan , Ming Lu , Rongfeng Lu , Zunjie Zhu

We introduce NovelGS, a diffusion model for Gaussian Splatting (GS) given sparse-view images. Recent works leverage feed-forward networks to generate pixel-aligned Gaussians, which could be fast rendered. Unfortunately, the method was…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Jinpeng Liu , Jiale Xu , Weihao Cheng , Yiming Gao , Xintao Wang , Ying Shan , Yansong Tang

Computational neuromorphic imaging (CNI) with event cameras offers advantages such as minimal motion blur and enhanced dynamic range, compared to conventional frame-based methods. Existing event-based radiance field rendering methods are…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Jingqian Wu , Shuo Zhu , Chutian Wang , Edmund Y. Lam

Event cameras, known for their high dynamic range, absence of motion blur, and low energy usage, have recently found a wide range of applications thanks to these attributes. In the past few years, the field of event-based 3D reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Hiroyuki Deguchi , Mana Masuda , Takuya Nakabayashi , Hideo Saito

In the domain of 3D scene representation, 3D Gaussian Splatting (3DGS) has emerged as a pivotal technology. However, its application to large-scale, high-resolution scenes (exceeding 4k$\times$4k pixels) is hindered by the excessive…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Wenkai Liu , Tao Guan , Bin Zhu , Lili Ju , Zikai Song , Dan Li , Yuesong Wang , Wei Yang

Gaze estimation encounters generalization challenges when dealing with out-of-distribution data. To address this problem, recent methods use neural radiance fields (NeRF) to generate augmented data. However, existing methods based on NeRF…

Computer Vision and Pattern Recognition · Computer Science 2025-07-10 Xiaobao Wei , Peng Chen , Guangyu Li , Ming Lu , Hui Chen , Feng Tian

3D Gaussian Splatting (3DGS) has demonstrated impressive capabilities in novel view synthesis. However, rendering reflective objects remains a significant challenge, particularly in inverse rendering and relighting. We introduce RTR-GS, a…

Graphics · Computer Science 2025-12-17 Yongyang Zhou , Fang-Lue Zhang , Zichen Wang , Lei Zhang

In low-light environments, conventional cameras often struggle to capture clear multi-view images of objects due to dynamic range limitations and motion blur caused by long exposure. Event cameras, with their high-dynamic range and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Jingqian Wu , Peiqi Duan , Zongqiang Wang , Changwei Wang , Boxin Shi , Edmund Y. Lam

Given a single image of a target object, image-to-3D generation aims to reconstruct its texture and geometric shape. Recent methods often utilize intermediate media, such as multi-view images or videos, to bridge the gap between input image…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Jiacheng Wang , Zhedong Zheng , Wei Xu , Ping Liu

3D Gaussian Splatting (3DGS) enables fast, high-quality novel view synthesis but typically relies on densification followed by pruning to optimize the number of Gaussians. Existing mask-based pruning, such as MaskGS, regularizes the global…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Ashkan Taghipour , Vahid Naghshin , Benjamin Southwell , Farid Boussaid , Hamid Laga , Mohammed Bennamoun