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We introduce SeaSplat, a method to enable real-time rendering of underwater scenes leveraging recent advances in 3D radiance fields. Underwater scenes are challenging visual environments, as rendering through a medium such as water…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Daniel Yang , John J. Leonard , Yogesh Girdhar

The recent success of 3D Gaussian Splatting (3DGS) has reshaped novel view synthesis by enabling fast optimization and real-time rendering of high-quality radiance fields. However, it relies on simplified, order-dependent alpha blending and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Jan U. Müller , Robin Tim Landsgesell , Leif Van Holland , Patrick Stotko , Reinhard Klein

3D Gaussian Splatting (3DGS) proposes an efficient solution for novel view synthesis. Its framework provides fast and high-fidelity rendering. Although less complex than other solutions such as Neural Radiance Fields (NeRF), there are still…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Stéphane Pateux , Matthieu Gendrin , Luce Morin , Théo Ladune , Xiaoran Jiang

We introduce AnySplat, a feed forward network for novel view synthesis from uncalibrated image collections. In contrast to traditional neural rendering pipelines that demand known camera poses and per scene optimization, or recent feed…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Lihan Jiang , Yucheng Mao , Linning Xu , Tao Lu , Kerui Ren , Yichen Jin , Xudong Xu , Mulin Yu , Jiangmiao Pang , Feng Zhao , Dahua Lin , Bo Dai

By combining differentiable rendering with explicit point-based scene representations, 3D Gaussian Splatting (3DGS) has demonstrated breakthrough 3D reconstruction capabilities. However, to date 3DGS has had limited impact on robotics,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Tianyi Xiong , Jiayi Wu , Botao He , Cornelia Fermuller , Yiannis Aloimonos , Heng Huang , Christopher A. Metzler

With their high-fidelity scene representation capability, the attention of SLAM field is deeply attracted by the Neural Radiation Field (NeRF) and 3D Gaussian Splatting (3DGS). Recently, there has been a surge in NeRF-based SLAM, while…

Computer Vision and Pattern Recognition · Computer Science 2024-06-03 Xinli Guo , Weidong Zhang , Ruonan Liu , Peng Han , Hongtian Chen

Image-based 3D reconstruction is a challenging task that involves inferring the 3D shape of an object or scene from a set of input images. Learning-based methods have gained attention for their ability to directly estimate 3D shapes. This…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Anurag Dalal , Daniel Hagen , Kjell G. Robbersmyr , Kristian Muri Knausgård

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

While the field of 3D scene reconstruction is dominated by NeRFs due to their photorealistic quality, 3D Gaussian Splatting (3DGS) has recently emerged, offering similar quality with real-time rendering speeds. However, both methods…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Jonas Kulhanek , Songyou Peng , Zuzana Kukelova , Marc Pollefeys , Torsten Sattler

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

LiDAR novel view synthesis (NVS) has emerged as a novel task within LiDAR simulation, offering valuable simulated point cloud data from novel viewpoints to aid in autonomous driving systems. However, existing LiDAR NVS methods typically…

Computer Vision and Pattern Recognition · Computer Science 2025-02-06 Junzhe Jiang , Chun Gu , Yurui Chen , Li Zhang

3D Gaussian Splatting algorithms excel in novel view rendering applications and have been adapted to extend the capabilities of traditional SLAM systems. However, current Gaussian Splatting SLAM methods, designed mainly for hand-held RGB or…

Robotics · Computer Science 2024-10-01 Zunjie Zhu , Youxu Fang , Xin Li , Chengang Yan , Feng Xu , Chau Yuen , Yanyan Li

Gaussian splatting methods are emerging as a popular approach for converting multi-view image data into scene representations that allow view synthesis. In particular, there is interest in enabling view synthesis for dynamic scenes using…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Yiqing Liang , Mikhail Okunev , Mikaela Angelina Uy , Runfeng Li , Leonidas Guibas , James Tompkin , Adam W. Harley

Ensuring the safety of autonomous robots, such as self-driving vehicles, requires extensive testing across diverse driving scenarios. Simulation is a key ingredient for conducting such testing in a cost-effective and scalable way. Neural…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Georg Hess , Carl Lindström , Maryam Fatemi , Christoffer Petersson , Lennart Svensson

Recent advancements in camera-based occupancy prediction have focused on the simultaneous prediction of 3D semantics and scene flow, a task that presents significant challenges due to specific difficulties, e.g., occlusions and unbalanced…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Ziyue Zhu , Shenlong Wang , Jin Xie , Jiang-jiang Liu , Jingdong Wang , Jian Yang

We present a portable multiscopic camera system with a dedicated model for novel view and time synthesis in dynamic scenes. Our goal is to render high-quality images for a dynamic scene from any viewpoint at any time using our portable…

Computer Vision and Pattern Recognition · Computer Science 2022-08-31 Tianjia Zhang , Yuen-Fui Lau , Qifeng Chen

3D Gaussian Splatting (3DGS) has shown remarkable potential for static scene reconstruction, and recent advancements have extended its application to dynamic scenes. However, the quality of reconstructions depends heavily on high-quality…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Yiren Lu , Yunlai Zhou , Disheng Liu , Tuo Liang , Yu Yin

Representing and rendering dynamic scenes has been an important but challenging task. Especially, to accurately model complex motions, high efficiency is usually hard to guarantee. To achieve real-time dynamic scene rendering while also…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Guanjun Wu , Taoran Yi , Jiemin Fang , Lingxi Xie , Xiaopeng Zhang , Wei Wei , Wenyu Liu , Qi Tian , Xinggang Wang

3D Gaussian Splatting (3DGS) has recently transformed photorealistic reconstruction, achieving high visual fidelity and real-time performance. However, rendering quality significantly deteriorates when test views deviate from the camera…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yutong Chen , Marko Mihajlovic , Xiyi Chen , Yiming Wang , Sergey Prokudin , Siyu Tang

This paper aims to tackle the problem of modeling dynamic urban streets for autonomous driving scenes. Recent methods extend NeRF by incorporating tracked vehicle poses to animate vehicles, enabling photo-realistic view synthesis of dynamic…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Yunzhi Yan , Haotong Lin , Chenxu Zhou , Weijie Wang , Haiyang Sun , Kun Zhan , Xianpeng Lang , Xiaowei Zhou , Sida Peng
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