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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

Recent breakthroughs in video generation, powered by large-scale datasets and diffusion techniques, have shown that video diffusion models can function as implicit 4D novel view synthesizers. Nevertheless, current methods primarily…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Yihao Zhi , Chenghong Li , Hongjie Liao , Xihe Yang , Zhengwentai Sun , Jiahao Chang , Xiaodong Cun , Wensen Feng , Xiaoguang Han

Novel view synthesis (NVS) in low-light scenes remains a significant challenge due to degraded inputs characterized by severe noise, low dynamic range (LDR) and unreliable initialization. While recent NeRF-based approaches have shown…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Hao Sun , Fenggen Yu , Huiyao Xu , Tao Zhang , Changqing Zou

Novel view synthesis from limited observations remains an important and persistent task. However, high efficiency in existing NeRF-based few-shot view synthesis is often compromised to obtain an accurate 3D representation. To address this…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Zehao Zhu , Zhiwen Fan , Yifan Jiang , Zhangyang Wang

Recent advances in feed-forward 3D Gaussian Splatting have led to rapid improvements in efficient scene reconstruction from sparse views. However, most existing approaches construct Gaussian primitives directly aligned with the pixels in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Yiming Wang , Lucy Chai , Xuan Luo , Michael Niemeyer , Manuel Lagunas , Stephen Lombardi , Siyu Tang , Tiancheng Sun

While 3D Vision Foundation Models (3DVFMs) have demonstrated remarkable zero-shot capabilities in visual geometry estimation, their direct application to generalizable novel view synthesis (NVS) remains challenging. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Minh-Quan Viet Bui , Jaeho Moon , Munchurl Kim

We present a novel framework for high-fidelity novel view synthesis (NVS) from sparse images, addressing key limitations in recent feed-forward 3D Gaussian Splatting (3DGS) methods built on Vision Transformer (ViT) backbones. While…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Yitong Dong , Qi Zhang , Minchao Jiang , Zhiqiang Wu , Qingnan Fan , Ying Feng , Huaqi Zhang , Hujun Bao , Guofeng Zhang

We introduce HyperGS, a novel framework for Hyperspectral Novel View Synthesis (HNVS), based on a new latent 3D Gaussian Splatting (3DGS) technique. Our approach enables simultaneous spatial and spectral renderings by encoding material…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Christopher Thirgood , Oscar Mendez , Erin Chao Ling , Jon Storey , Simon Hadfield

We present MS-Splatting -- a multi-spectral 3D Gaussian Splatting (3DGS) framework that is able to generate multi-view consistent novel views from images of multiple, independent cameras with different spectral domains. In contrast to…

Graphics · Computer Science 2026-02-17 Lukas Meyer , Josef Grün , Maximilian Weiherer , Bernhard Egger , Marc Stamminger , Linus Franke

Recently, 3D Gaussian Splatting (3DGS) has exceled in novel view synthesis (NVS) with its real-time rendering capabilities and superior quality. However, it faces challenges for high-resolution novel view synthesis (HRNVS) due to the coarse…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Shiyun Xie , Zhiru Wang , Xu Wang , Yinghao Zhu , Chengwei Pan , Xiwang Dong

3D Gaussian Splatting (3DGS) has demonstrated impressive performance in synthesizing novel views after training on a given set of viewpoints. However, its rendering quality deteriorates when the synthesized view deviates significantly from…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Jiatong Xia , Lingqiao Liu

Generating novel views of a natural scene, e.g., every-day scenes both indoors and outdoors, from a single view is an under-explored problem, even though it is an organic extension to the object-centric novel view synthesis. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 Wonbong Jang , Jonathan Tremblay , Lourdes Agapito

3D reconstruction and view synthesis are foundational problems in computer vision, graphics, and immersive technologies such as augmented reality (AR), virtual reality (VR), and digital twins. Traditional methods rely on computationally…

Underwater scene reconstruction is essential for immersive exploration of aquatic environments, yet remains challenging due to complex participating-media effects such as absorption and scattering, as well as the limited field of view (FoV)…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Jiangbei Hu , Weichao Song , Shibo Yu , Mohan Wang , Zihan Yi , Rui Wu , Mingkang Xiang , Na Lei , Shengfa Wang , Zhongxuan Luo , Ying He

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

Reconstructing 3D scenes from sparse viewpoints is a long-standing challenge with wide applications. Recent advances in feed-forward 3D Gaussian sparse-view reconstruction methods provide an efficient solution for real-time novel view…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Yang Xiao , Guoan Xu , Qiang Wu , Wenjing Jia

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 advances in radiance field reconstruction, such as 3D Gaussian Splatting (3DGS), have achieved high-quality novel view synthesis and fast rendering by representing scenes with compositions of Gaussian primitives. However, 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Jan Held , Renaud Vandeghen , Abdullah Hamdi , Adrien Deliege , Anthony Cioppa , Silvio Giancola , Andrea Vedaldi , Bernard Ghanem , Marc Van Droogenbroeck

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

Scenes reconstructed by 3D Gaussian Splatting (3DGS) trained on low-resolution (LR) images are unsuitable for high-resolution (HR) rendering. Consequently, a 3DGS super-resolution (SR) method is needed to bridge LR inputs and HR rendering.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-18 Kaizhe Zhang , Shinan Chen , Qian Zhao , Weizhan Zhang , Caixia Yan , Yudeng Xin
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