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Online novel view synthesis remains challenging, requiring robust scene reconstruction from sequential, often unposed, observations. We present ReCoSplat, an autoregressive feed-forward Gaussian Splatting model supporting posed or unposed…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Freeman Cheng , Botao Ye , Xueting Li , Junqi You , Fangneng Zhan , Ming-Hsuan Yang

3D Gaussian Splatting achieves high-fidelity novel view synthesis, but its application to online long-sequence scenarios is still limited. Existing methods either rely on slow per-scene optimization or fail to provide efficient incremental…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Guichen Huang , Ruoyu Wang , Xiangjun Gao , Che Sun , Yuwei Wu , Shenghua Gao , Yunde Jia

Despite the substantial progress of novel view synthesis, existing methods, either based on the Neural Radiance Fields (NeRF) or more recently 3D Gaussian Splatting (3DGS), suffer significant degradation when the input becomes sparse.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-07 Rui Peng , Wangze Xu , Luyang Tang , Liwei Liao , Jianbo Jiao , Ronggang Wang

3D Language Gaussian Splatting (3DLGS) augments 3D Gaussian Splatting with language-aligned visual features for open-vocabulary 3D scene understanding. A core challenge is efficiently associating high-dimensional vision-language embeddings…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Lovre Antonio Budimir , Yushi Guan , Steve Ryhner , Sven Lončarić , Nandita Vijaykumar

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

3D Gaussian Splatting (3DGS) has emerged as a powerful technique for radiance field rendering, but it typically requires millions of redundant Gaussian primitives, overwhelming memory and rendering budgets. Existing compaction approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Tao Wang , Mengyu Li , Geduo Zeng , Cheng Meng , Qiong Zhang

We consider the problem of novel view synthesis from unposed images in a single feed-forward. Our framework capitalizes on fast speed, scalability, and high-quality 3D reconstruction and view synthesis capabilities of 3DGS, where we further…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Sunghwan Hong , Jaewoo Jung , Heeseong Shin , Jisang Han , Jiaolong Yang , Chong Luo , Seungryong Kim

We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

Computer Vision and Pattern Recognition · Computer Science 2025-07-02 Xingjun Wang , Lianlei Shan

We present Splat-SAP, a feed-forward approach to render novel views of human-centered scenes from binocular cameras with large sparsity. Gaussian Splatting has shown its promising potential in rendering tasks, but it typically necessitates…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Boyao Zhou , Shunyuan Zheng , Zhanfeng Liao , Zihan Ma , Hanzhang Tu , Boning Liu , Yebin Liu

Feed-forward 3D reconstruction for autonomous driving has advanced rapidly, yet existing methods struggle with the joint challenges of sparse, non-overlapping camera views and complex scene dynamics. We present UniSplat, a general…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Chen Shi , Shaoshuai Shi , Xiaoyang Lyu , Chunyang Liu , Kehua Sheng , Bo Zhang , Li Jiang

The recent advent of 3D Gaussian Splatting (3DGS) has revolutionized the 3D scene reconstruction space enabling high-fidelity novel view synthesis in real-time. However, with the exception of RawNeRF, all prior 3DGS and NeRF-based methods…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Shreyas Singh , Aryan Garg , Kaushik Mitra

Feed-forward 3D Gaussian splatting (3DGS) models have gained significant popularity due to their ability to generate scenes immediately without needing per-scene optimization. Although omnidirectional images are becoming more popular since…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Suyoung Lee , Jaeyoung Chung , Kihoon Kim , Jaeyoo Huh , Gunhee Lee , Minsoo Lee , Kyoung Mu Lee

3D Gaussian Splatting (3DGS) has emerged as a powerful paradigm for real-time and high-fidelity 3D reconstruction from posed images. However, recent studies reveal its vulnerability to adversarial corruptions in input views, where…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Yiran Qiao , Yiren Lu , Yunlai Zhou , Rui Yang , Linlin Hou , Yu Yin , Jing Ma

High-fidelity 3D Gaussian Splatting methods excel at capturing fine textures but often overlook model compactness, resulting in massive splat counts, bloated memory, long training, and complex post-processing. We present Micro-Splatting:…

Graphics · Computer Science 2025-09-03 Jee Won Lee , Hansol Lim , Sooyeun Yang , Jongseong Brad Choi

Empowering 3D Gaussian Splatting with generalization ability is appealing. However, existing generalizable 3D Gaussian Splatting methods are largely confined to narrow-range interpolation between stereo images due to their heavy backbones,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Yunsong Wang , Tianxin Huang , Hanlin Chen , Gim Hee Lee

Recent advancements in 3D Gaussian Splatting (3DGS) have demonstrated its potential for efficient and photorealistic 3D reconstructions, which is crucial for diverse applications such as robotics and immersive media. However, current…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Daheng Yin , Isaac Ding , Yili Jin , Jianxin Shi , Jiangchuan Liu

Feedforward 3D Gaussian Splatting (3DGS) overcomes the limitations of optimization-based 3DGS by enabling fast and high-quality reconstruction without the need for per-scene optimization. However, existing feedforward approaches typically…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Anran Wu , Long Peng , Xin Di , Xueyuan Dai , Chen Wu , Yang Wang , Xueyang Fu , Yang Cao , Zheng-Jun Zha

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

Recent advances in novel view synthesis have enabled real-time rendering speeds with high reconstruction accuracy. 3D Gaussian Splatting (3D-GS), a foundational point-based parametric 3D scene representation, models scenes as large sets of…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Alex Hanson , Allen Tu , Vasu Singla , Mayuka Jayawardhana , Matthias Zwicker , Tom Goldstein

Gaussian Splatting and its dynamic extensions are effective for reconstructing 3D scenes from 2D images when there is significant camera movement to facilitate motion parallax and when scene objects remain relatively static. However, in…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Liuyue Xie , Joel Julin , Koichiro Niinuma , Laszlo A. Jeni