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In underwater images, most useful features are occluded by water. The extent of the occlusion depends on imaging geometry and can vary even across a sequence of burst images. As a result, 3D reconstruction methods robust on in-air scenes,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Nir Mualem , Roy Amoyal , Oren Freifeld , Derya Akkaynak

Neural Radiance Fields (NeRFs) have demonstrated remarkable potential in capturing complex 3D scenes with high fidelity. However, one persistent challenge that hinders the widespread adoption of NeRFs is the computational bottleneck due to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-16 Joo Chan Lee , Daniel Rho , Xiangyu Sun , Jong Hwan Ko , Eunbyung Park

3D Gaussian Splatting is emerging as a state-of-the-art technique in novel view synthesis, recognized for its impressive balance between visual quality, speed, and rendering efficiency. However, reliance on third-degree spherical harmonics…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Yiwen Wang , Siyuan Chen , Ran Yi

Over the past year, 3D Gaussian Splatting (3DGS) has received significant attention for its ability to represent 3D scenes in a perceptually accurate manner. However, it can require a substantial amount of storage since each splat's…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Brent Zoomers , Maarten Wijnants , Ivan Molenaers , Joni Vanherck , Jeroen Put , Lode Jorissen , Nick Michiels

Modern vision language pipelines are driven by RGB vision encoders trained on massive image text corpora. While these pipelines have enabled impressive zero-shot capabilities and strong transfer across tasks, they still inherit two…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Yasmine Omri , Connor Ding , Tsachy Weissman , Thierry Tambe

2D Gaussian Splatting (2DGS) is an emerging explicit scene representation method with significant potential for image compression due to high fidelity and high compression ratios. However, existing low-light enhancement algorithms operate…

Computer Vision and Pattern Recognition · Computer Science 2026-01-23 Yuhan Chen , Wenxuan Yu , Guofa Li , Yijun Xu , Ying Fang , Yicui Shi , Long Cao , Wenbo Chu , Keqiang Li

Efficient neural representations for dynamic video scenes are critical for applications ranging from video compression to interactive simulations. Yet, existing methods often face challenges related to high memory usage, lengthy training…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Andrew Bond , Jui-Hsien Wang , Long Mai , Erkut Erdem , Aykut Erdem

3D Gaussian Splatting (3DGS) has emerged as a powerful representation for real-time, high-performance rendering, enabling a wide range of applications. However, representing 3D scenes with numerous explicit Gaussian primitives imposes…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Joo Chan Lee , Jong Hwan Ko , Eunbyung Park

Gaussian splatting, renowned for its exceptional rendering quality and efficiency, has emerged as a prominent technique in 3D scene representation. However, the substantial data volume of Gaussian splatting impedes its practical utility in…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Xiangrui Liu , Xinju Wu , Pingping Zhang , Shiqi Wang , Zhu Li , Sam Kwong

Neural scene representations, such as 3D Gaussian Splatting (3DGS), have enabled high-quality neural rendering; however, their large storage and transmission costs hinder deployment in resource-constrained environments. Existing compression…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Jiaqi Chen , Xinhao Ji , Yuanyuan Gao , Hao Li , Yuning Gong , Yifei Liu , Dan Xu , Zhihang Zhong , Dingwen Zhang , Xiao Sun

Gaussian Splatting (GS), a recent technique for converting discrete points into continuous spatial representations, has shown promising results in 3D scene modeling and 2D image super-resolution. In this paper, we explore its untapped…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Hongyu Li , Chaofeng Chen , Xiaoming Li , Guangming Lu

Arbitrary-scale super-resolution (ASSR) aims to reconstruct high-resolution (HR) images from low-resolution (LR) inputs with arbitrary upsampling factors using a single model, addressing the limitations of traditional SR methods constrained…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Long Peng , Anran Wu , Wenbo Li , Peizhe Xia , Xueyuan Dai , Xinjie Zhang , Xin Di , Haoze Sun , Renjing Pei , Yang Wang , Yang Cao , Zheng-Jun Zha

We present the first unified framework for rate-distortion-optimized compression and segmentation of 3D Gaussian Splatting (3DGS). While 3DGS has proven effective for both real-time rendering and semantic scene understanding, prior works…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Yu-Jen Tseng , Chia-Hao Kao , Jing-Zhong Chen , Alessandro Gnutti , Shao-Yuan Lo , Yen-Yu Lin , Wen-Hsiao Peng

3D Gaussian Splatting (3DGS) has demonstrated remarkable effectiveness in 3D reconstruction, achieving high-quality results with real-time radiance field rendering. However, a key challenge is the substantial storage cost: reconstructing a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Haishan Wang , Mohammad Hassan Vali , Arno Solin

Compression techniques for 3D Gaussian Splatting (3DGS) have recently achieved considerable success in minimizing storage overhead for 3D Gaussians while preserving high rendering quality. Despite the impressive storage reduction, the lack…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Seungjoo Shin , Jaesik Park , Sunghyun Cho

Implicit Neural Representations (INRs) employ neural networks to approximate discrete data as continuous functions. In the context of video data, such models can be utilized to transform the coordinates of pixel locations along with frame…

Computer Vision and Pattern Recognition · Computer Science 2026-02-19 Weronika Smolak-Dyżewska , Dawid Malarz , Kornel Howil , Jan Kaczmarczyk , Marcin Mazur , Przemysław Spurek

3D Gaussian Splatting (3DGS) achieves impressive quality and rendering speed, but with millions of 3D Gaussians and significant storage and transmission costs. In this paper, we aim to develop a simple yet effective method called NeuralGS…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Zhenyu Tang , Chaoran Feng , Xinhua Cheng , Wangbo Yu , Junwu Zhang , Yuan Liu , Xiaoxiao Long , Wenping Wang , Li Yuan

3D Gaussians have recently emerged as a highly efficient representation for 3D reconstruction and rendering. Despite its high rendering quality and speed at high resolutions, they both deteriorate drastically when rendered at lower…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Zhiwen Yan , Weng Fei Low , Yu Chen , Gim Hee Lee

3D Gaussian Splatting represents a breakthrough in the field of novel view synthesis. It establishes Gaussians as core rendering primitives for highly accurate real-world environment reconstruction. Recent advances have drastically…

Graphics · Computer Science 2025-06-25 Jonathan Haberl , Philipp Fleck , Clemens Arth

The computer vision and image processing research community has been involved in standardizing video data communications for the past many decades, leading to standards such as AVC, HEVC, VVC, AV1, AV2, etc. However, recent groundbreaking…

Computer Vision and Pattern Recognition · Computer Science 2025-05-15 Lakshya Gupta , Imran N. Junejo