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3D Gaussian Splatting (3DGS) has demonstrated remarkable effectiveness in novel view synthesis (NVS). However, 3DGS tends to overfit when trained with sparse views, limiting its generalization to novel viewpoints. In this paper, we address…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Chen Zhao , Xuan Wang , Tong Zhang , Saqib Javed , Mathieu Salzmann

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

Novel view synthesis (NVS) through non-planar refractive surfaces presents fundamental challenges due to severe, spatially varying optical distortions. While recent representations like NeRF and 3D Gaussian Splatting (3DGS) excel at NVS,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yiming Shao , Qiyu Dai , Chong Gao , Guanbin Li , Yeqiang Wang , He Sun , Qiong Zeng , Baoquan Chen , Wenzheng Chen

Dynamic Gaussian splatting has led to impressive scene reconstruction and image synthesis advances in novel views. Existing methods, however, heavily rely on pre-computed poses and Gaussian initialization by Structure from Motion (SfM)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Hao Li , Jingfeng Li , Dingwen Zhang , Chenming Wu , Jieqi Shi , Chen Zhao , Haocheng Feng , Errui Ding , Jingdong Wang , Junwei Han

Drones have become essential tools for reconstructing wild scenes due to their outstanding maneuverability. Recent advances in radiance field methods have achieved remarkable rendering quality, providing a new avenue for 3D reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Jiadong Tang , Yu Gao , Dianyi Yang , Liqi Yan , Yufeng Yue , Yi Yang

3D Gaussian Splatting (3DGS) has demonstrated its potential in reconstructing scenes from unposed images. However, optimization-based 3DGS methods struggle with sparse views due to limited prior knowledge. Meanwhile, feed-forward Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Chong Cheng , Yu Hu , Sicheng Yu , Beizhen Zhao , Zijian Wang , Hao Wang

We propose GRGS, a generalizable and relightable 3D Gaussian framework for high-fidelity human novel view synthesis under diverse lighting conditions. Unlike existing methods that rely on per-character optimization or ignore physical…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Yipengjing Sun , Shengping Zhang , Chenyang Wang , Shunyuan Zheng , Zonglin Li , Xiangyang Ji

This paper investigates an open research challenge of reconstructing high-quality, large 3D open scenes from images. It is observed existing methods have various limitations, such as requiring precise camera poses for input and dense…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Chong Cheng , Gaochao Song , Yiyang Yao , Qinzheng Zhou , Gangjian Zhang , Hao Wang

Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a practical and scalable reconstruction method,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Marko Mihajlovic , Sergey Prokudin , Siyu Tang , Robert Maier , Federica Bogo , Tony Tung , Edmond Boyer

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

3D Gaussian splatting (3DGS) is an innovative rendering technique that surpasses the neural radiance field (NeRF) in both rendering speed and visual quality by leveraging an explicit 3D scene representation. Existing 3DGS approaches require…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Lintao Xiang , Hongpei Zheng , Yating Huang , Qijun Yang , Hujun Yin

Differentiable rendering techniques have recently shown promising results for free-viewpoint video synthesis of characters. However, such methods, either Gaussian Splatting or neural implicit rendering, typically necessitate per-subject…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Boyao Zhou , Shunyuan Zheng , Hanzhang Tu , Ruizhi Shao , Boning Liu , Shengping Zhang , Liqiang Nie , Yebin Liu

Novel View Synthesis (NVS) from sparse views presents a formidable challenge in 3D reconstruction, where limited multi-view constraints lead to severe overfitting, geometric distortion, and fragmented scenes. While 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Yu Ma , Guoliang Wei , Haihong Xiao , Yue Cheng

Sparse-view synthesis remains a challenging problem due to the difficulty of recovering accurate geometry and appearance from limited observations. While recent advances in 3D Gaussian Splatting (3DGS) have enabled real-time rendering with…

Computer Vision and Pattern Recognition · Computer Science 2025-11-19 Yi-Hsin Li , Thomas Sikora , Sebastian Knorr , Mårten Sjöström

3D Gaussian Splatting (3DGS) is a highly deployable real-time method for novel view synthesis. In practice, it requires a universal, consistent control mechanism that adjusts the trade-off between rendering quality and model compression…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Fengdi Zhang , Yibao Sun , Hongkun Cao , Ruqi Huang

3D Gaussian Splatting (3DGS) enables high-quality novel view synthesis, motivating interest in generating higher-resolution renders than those available during training. A natural strategy is to apply super-resolution (SR) to low-resolution…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Pranav Asthana , Alex Hanson , Allen Tu , Tom Goldstein , Matthias Zwicker , Amitabh Varshney

This paper presents DENSER, an efficient and effective approach leveraging 3D Gaussian splatting (3DGS) for the reconstruction of dynamic urban environments. While several methods for photorealistic scene representations, both implicitly…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Mahmud A. Mohamad , Gamal Elghazaly , Arthur Hubert , Raphael Frank

Recently, 3D Gaussian Splatting and its derivatives have achieved significant breakthroughs in large-scale scene reconstruction. However, how to efficiently and stably achieve high-quality geometric fidelity remains a core challenge. To…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Kehua Chen , Tianlu Mao , Xinzhu Ma , Hao Jiang , Zehao Li , Zihan Liu , Shuqin Gao , Honglong Zhao , Feng Dai , Yucheng Zhang , Zhaoqi Wang

3D scene reconstruction under unposed sparse viewpoints is a highly challenging yet practically important problem, especially in outdoor scenes due to complex lighting and scale variation. With extremely limited input views, directly…

Computer Vision and Pattern Recognition · Computer Science 2026-02-26 Beizhen Zhao , Sicheng Yu , Guanzhi Ding , Yu Hu , Hao Wang

3D Gaussian Splatting (3DGS) has transformed novel-view synthesis with its fast, interpretable, and high-fidelity rendering. However, its resource requirements limit its usability. Especially on constrained devices, training performance…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Saswat Subhajyoti Mallick , Rahul Goel , Bernhard Kerbl , Francisco Vicente Carrasco , Markus Steinberger , Fernando De La Torre