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Three-dimensional reconstruction in scenes with extreme depth variations remains challenging due to inconsistent supervisory signals between near-field and far-field regions. Existing methods fail to simultaneously address inaccurate depth…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Yu Deng , Baozhu Zhao , Junyan Su , Xiaohan Zhang , Qi Liu

We introduce OceanSplat, a novel 3D Gaussian Splatting-based approach for high-fidelity underwater scene reconstruction. To overcome multi-view inconsistencies caused by scattering media, we design a trinocular setup for each camera pose by…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Minseong Kweon , Jinsun Park

3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis results while advancing real-time rendering performance. However, it relies heavily on the quality of the initial point cloud, resulting in blurring and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Zheng Zhang , Wenbo Hu , Yixing Lao , Tong He , Hengshuang Zhao

Generalizable Gaussian Splatting aims to synthesize novel views for unseen scenes without per-scene optimization. In particular, recent advancements utilize feed-forward networks to predict per-pixel Gaussian parameters, enabling…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Yuxi Hu , Jun Zhang , Kuangyi Chen , Zhe Zhang , Friedrich Fraundorfer

Synthesizing novel views of large-scale scenes from unconstrained in-the-wild images is an important but challenging task in computer vision. Existing methods, which optimize per-image appearance and transient occlusion through implicit…

Computer Vision and Pattern Recognition · Computer Science 2026-02-02 Yiqing Li , Xuan Wang , Jiawei Wu , Yikun Ma , Zhi Jin

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

Sparse-view reconstruction with 3D Gaussian Splatting (3DGS) is fundamentally ill-posed due to insufficient geometric supervision, often leading to severe overfitting and the emergence of structural distortions and translucent haze-like…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Hantang Li , Qiang Zhu , Xiandong Meng , Debin Zhao , Xiaopeng Fan

Novel view synthesis from raw images provides superior high dynamic range (HDR) information compared to reconstructions from low dynamic range RGB images. However, the inherent noise in unprocessed raw images compromises the accuracy of 3D…

Image and Video Processing · Electrical Eng. & Systems 2024-06-13 Zhihao Li , Yufei Wang , Alex Kot , Bihan Wen

Recently, 3D Gaussian splatting has gained attention for its capability to generate high-fidelity rendering results. At the same time, most applications such as games, animation, and AR/VR use mesh-based representations to represent and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Jaehoon Choi , Yonghan Lee , Hyungtae Lee , Heesung Kwon , Dinesh Manocha

While 3D Gaussian Splatting (3DGS) achieves real-time photorealistic rendering, its performance degrades significantly when training images contain transient objects that violate multi-view consistency. Existing methods face a circular…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Xu Wang , Zhiru Wang , Shiyun Xie , Chengwei Pan , Yisong Chen

3D Gaussian Splatting (3DGS) has emerged as a promising 3D reconstruction technique. The traditional 3DGS training pipeline follows three sequential steps: Gaussian densification, Gaussian projection, and color splatting. Despite its…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Junyi Wu , Jiaming Xu , Jinhao Li , Yongkang Zhou , Jiayi Pan , Xingyang Li , Guohao Dai

3D Gaussian Splatting (3DGS) has established itself as a leading technique for 3D reconstruction and novel view synthesis of static scenes, achieving outstanding rendering quality and fast training. However, the method does not explicitly…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Margherita Lea Corona , Wieland Morgenstern , Peter Eisert , Anna Hilsmann

We present a multispectral extension to 3D Gaussian Splatting (3DGS) for wavelength-aware view synthesis. Each Gaussian is augmented with spectral radiance, represented via per-band spherical harmonics, and optimized under a dual-loss…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Iris Zheng , Guojun Tang , Alexander Doronin , Paul Teal , Fang-Lue Zhang

Rendering and reconstruction are long-standing topics in computer vision and graphics. Achieving both high rendering quality and accurate geometry is a challenge. Recent advancements in 3D Gaussian Splatting (3DGS) have enabled…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Meng Wei , Qianyi Wu , Jianmin Zheng , Hamid Rezatofighi , Jianfei Cai

3D Gaussian Splatting has advanced radiance field reconstruction, enabling high-quality view synthesis and fast rendering in 3D modeling. While adversarial attacks on object detection models are well-studied for 2D images, their impact on…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Abdurrahman Zeybey , Mehmet Ergezer , Tommy Nguyen

3D Gaussian Splatting (3DGS) enables high-fidelity real-time rendering, a key requirement for immersive applications. However, the extension of 3DGS to dynamic scenes remains limitations on the substantial data volume of dense Gaussians and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Jiayu Yang , Weijian Su , Songqian Zhang , Yuqi Han , Jinli Suo , Qiang Zhang

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

We propose WildSplatter, a feed-forward 3D Gaussian Splatting (3DGS) model for unconstrained images with unknown camera parameters and varying lighting conditions. 3DGS is an effective scene representation that enables high-quality,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Yuki Fujimura , Takahiro Kushida , Kazuya Kitano , Takuya Funatomi , Yasuhiro Mukaigawa

Photographs captured in unstructured tourist environments frequently exhibit variable appearances and transient occlusions, challenging accurate scene reconstruction and inducing artifacts in novel view synthesis. Although prior approaches…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Jiacong Xu , Yiqun Mei , Vishal M. Patel

Recent advancements in 3D Gaussian Splatting(3DGS) have significantly improved semantic scene understanding, enabling natural language queries to localize objects within a scene. However, existing methods primarily focus on embedding…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Xihan Wang , Dianyi Yang , Yu Gao , Yufeng Yue , Yi Yang , Mengyin Fu
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