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3D Gaussian Splatting (3DGS) has recently unlocked real-time, high-fidelity novel view synthesis by representing scenes using explicit 3D primitives. However, traditional methods often require millions of Gaussians to capture complex…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Anh Thuan Tran , Jana Kosecka

Gaussian Splatting has achieved remarkable progress in multi-view surface reconstruction, yet it exhibits notable degradation when only few views are available. Although recent efforts alleviate this issue by enhancing multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Jimin Tang , Wenyuan Zhang , Junsheng Zhou , Zian Huang , Kanle Shi , Shenkun Xu , Yu-Shen Liu , Zhizhong Han

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

Compared with previous 3D reconstruction methods like Nerf, recent Generalizable 3D Gaussian Splatting (G-3DGS) methods demonstrate impressive efficiency even in the sparse-view setting. However, the promising reconstruction performance of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Chuanrui Zhang , Yingshuang Zou , Zhuoling Li , Minmin Yi , Haoqian Wang

3D Gaussians have recently emerged as an effective scene representation for real-time splatting and accurate novel-view synthesis, motivating several works to adapt multi-view structure prediction networks to regress per-pixel 3D Gaussians…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Mehdi Hosseinzadeh , Shin-Fang Chng , Yi Xu , Simon Lucey , Ian Reid , Ravi Garg

Sparse-view reconstruction models typically require precise camera poses, yet obtaining these parameters from sparse-view images remains challenging. We introduce FreeSplatter, a scalable feed-forward framework that generates high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Jiale Xu , Shenghua Gao , Ying Shan

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

Feed-forward 3D Gaussian Splatting methods enable single-pass reconstruction and real-time rendering. However, they typically adopt rigid pixel-to-Gaussian or voxel-to-Gaussian pipelines that uniformly allocate Gaussians, leading to…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Injae Kim , Chaehyeon Kim , Minseong Bae , Minseok Joo , Hyunwoo J. Kim

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

Fast and flexible 3D scene reconstruction from unstructured image collections remains a significant challenge. We present YoNoSplat, a feedforward model that reconstructs high-quality 3D Gaussian Splatting representations from an arbitrary…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Botao Ye , Boqi Chen , Haofei Xu , Daniel Barath , Marc Pollefeys

Reconstructing 3D scenes from multiple viewpoints is a fundamental task in stereo vision. Recently, advances in generalizable 3D Gaussian Splatting have enabled high-quality novel view synthesis for unseen scenes from sparse input views by…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Shengji Tang , Weicai Ye , Peng Ye , Weihao Lin , Yang Zhou , Tao Chen , Wanli Ouyang

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

Recent advances in 3D Gaussian Splatting (3DGS) have enabled significant progress in photorealistic novel view synthesis. However, traditional 3DGS relies on a slow, iterative optimization process, which limits its use in scenarios…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Can Wang , Lei Liu , Wei Jiang , Dong Xu

In computer graphics and vision, recovering easily modifiable scene appearance from image data is crucial for applications such as content creation. We introduce a novel method that integrates 3D Gaussian Splatting with an implicit surface…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Jakub Szymkowiak , Weronika Jakubowska , Dawid Malarz , Weronika Smolak-Dyżewska , Maciej Zięba , Przemyslaw Musialski , Wojtek Pałubicki , Przemysław Spurek

Novel view synthesis of urban scenes is essential for autonomous driving-related applications.Existing NeRF and 3DGS-based methods show promising results in achieving photorealistic renderings but require slow, per-scene optimization. We…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Sheng Miao , Jiaxin Huang , Dongfeng Bai , Xu Yan , Hongyu Zhou , Yue Wang , Bingbing Liu , Andreas Geiger , Yiyi Liao

This paper presents a pose-free, feed-forward 3D Gaussian Splatting (3DGS) framework designed to handle unfavorable input views. A common rendering setup for training feed-forward approaches places a 3D object at the world origin and…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Yuki Fujimura , Takahiro Kushida , Kazuya Kitano , Takuya Funatomi , Yasuhiro Mukaigawa

Differentiable rendering with 3D Gaussian primitives has emerged as a powerful method for reconstructing high-fidelity 3D scenes from multi-view images. While it offers improvements over NeRF-based methods, this representation still…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Kaifeng Sheng , Zheng Zhou , Yingliang Peng , Qianwei Wang

We introduce MVSplat360, a feed-forward approach for 360{\deg} novel view synthesis (NVS) of diverse real-world scenes, using only sparse observations. This setting is inherently ill-posed due to minimal overlap among input views and…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Yuedong Chen , Chuanxia Zheng , Haofei Xu , Bohan Zhuang , Andrea Vedaldi , Tat-Jen Cham , Jianfei Cai

We propose Flash3D, a method for scene reconstruction and novel view synthesis from a single image which is both very generalisable and efficient. For generalisability, we start from a "foundation" model for monocular depth estimation and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Stanislaw Szymanowicz , Eldar Insafutdinov , Chuanxia Zheng , Dylan Campbell , João F. Henriques , Christian Rupprecht , Andrea Vedaldi

Creating 3D assets from single-view images is a complex task that demands a deep understanding of the world. Recently, feed-forward 3D generative models have made significant progress by training large reconstruction models on extensive 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Wenqiang Sun , Zhengyi Wang , Shuo Chen , Yikai Wang , Zilong Chen , Jun Zhu , Jun Zhang