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We introduce a method for using event camera data in novel view synthesis via Gaussian Splatting. Event cameras offer exceptional temporal resolution and a high dynamic range. Leveraging these capabilities allows us to effectively address…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Toshiya Yura , Ashkan Mirzaei , Igor Gilitschenski

Gaussian Splatting (GS) has significantly elevated scene reconstruction efficiency and novel view synthesis (NVS) accuracy compared to Neural Radiance Fields (NeRF), particularly for dynamic scenes. However, current 4D NVS methods, whether…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Fang Li , Hao Zhang , Narendra Ahuja

In this study, we present a method for synthesizing novel views from a single 360-degree RGB-D image based on the neural radiance field (NeRF) . Prior studies relied on the neighborhood interpolation capability of multi-layer perceptrons to…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Takayuki Hara , Tatsuya Harada

Neural Radiance Fields (NeRFs) have become increasingly popular because of their impressive ability for novel view synthesis. However, their effectiveness is hindered by the Rolling Shutter (RS) effects commonly found in most camera…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Muyao Niu , Tong Chen , Yifan Zhan , Zhuoxiao Li , Xiang Ji , Yinqiang Zheng

Novel View Synthesis (NVS) for street scenes play a critical role in the autonomous driving simulation. The current mainstream technique to achieve it is neural rendering, such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Zhongrui Yu , Haoran Wang , Jinze Yang , Hanzhang Wang , Zeke Xie , Yunfeng Cai , Jiale Cao , Zhong Ji , Mingming Sun

We present a new neural representation, called Neural Ray (NeuRay), for the novel view synthesis task. Recent works construct radiance fields from image features of input views to render novel view images, which enables the generalization…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Yuan Liu , Sida Peng , Lingjie Liu , Qianqian Wang , Peng Wang , Christian Theobalt , Xiaowei Zhou , Wenping Wang

Neural Radiance Fields (NeRFs) have emerged as powerful tools for capturing detailed 3D scenes through continuous volumetric representations. Recent NeRFs utilize feature grids to improve rendering quality and speed; however, these…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Tuan Pham , Stephan Mandt

The field of 3D reconstruction from images has rapidly evolved in the past few years, first with the introduction of Neural Radiance Field (NeRF) and more recently with 3D Gaussian Splatting (3DGS). The latter provides a significant edge…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Avinash Paliwal , Wei Ye , Jinhui Xiong , Dmytro Kotovenko , Rakesh Ranjan , Vikas Chandra , Nima Khademi Kalantari

Neural Radiance Fields (NeRF) are able to reconstruct scenes with unprecedented fidelity, and various recent works have extended NeRF to handle dynamic scenes. A common approach to reconstruct such non-rigid scenes is through the use of a…

Computer Vision and Pattern Recognition · Computer Science 2021-09-13 Keunhong Park , Utkarsh Sinha , Peter Hedman , Jonathan T. Barron , Sofien Bouaziz , Dan B Goldman , Ricardo Martin-Brualla , Steven M. Seitz

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

Neural rendering techniques combining machine learning with geometric reasoning have arisen as one of the most promising approaches for synthesizing novel views of a scene from a sparse set of images. Among these, stands out the Neural…

Computer Vision and Pattern Recognition · Computer Science 2020-12-01 Albert Pumarola , Enric Corona , Gerard Pons-Moll , Francesc Moreno-Noguer

Asynchronously operating event cameras find many applications due to their high dynamic range, vanishingly low motion blur, low latency and low data bandwidth. The field saw remarkable progress during the last few years, and existing…

Computer Vision and Pattern Recognition · Computer Science 2023-03-27 Viktor Rudnev , Mohamed Elgharib , Christian Theobalt , Vladislav Golyanik

Recent works in volume rendering, \textit{e.g.} NeRF and 3D Gaussian Splatting (3DGS), significantly advance the rendering quality and efficiency with the help of the learned implicit neural radiance field or 3D Gaussians. Rendering on top…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Xiaobiao Du , Yida Wang , Xin Yu

The emergence of Neural Radiance Fields (NeRF) for novel view synthesis has increased interest in 3D scene editing. An essential task in editing is removing objects from a scene while ensuring visual reasonability and multiview consistency.…

Computer Vision and Pattern Recognition · Computer Science 2023-10-02 Youtan Yin , Zhoujie Fu , Fan Yang , Guosheng Lin

Neural Radiance Fields (NeRF) achieve photo-realistic view synthesis with densely captured input images. However, the geometry of NeRF is extremely under-constrained given sparse views, resulting in significant degradation of novel view…

Computer Vision and Pattern Recognition · Computer Science 2022-09-13 Zheng Chen , Chen Wang , Yuan-Chen Guo , Song-Hai Zhang

This paper introduces a novel continual learning framework for synthesising novel views of multiple scenes, learning multiple 3D scenes incrementally, and updating the network parameters only with the training data of the upcoming new…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Yuze Wang , Junyi Wang , Chen Wang , Wantong Duan , Yongtang Bao , Yue Qi

Photo-realistic free-viewpoint rendering of real-world scenes using classical computer graphics techniques is challenging, because it requires the difficult step of capturing detailed appearance and geometry models. Recent studies have…

Computer Vision and Pattern Recognition · Computer Science 2021-01-08 Lingjie Liu , Jiatao Gu , Kyaw Zaw Lin , Tat-Seng Chua , Christian Theobalt

Volumetric neural rendering methods like NeRF generate high-quality view synthesis results but are optimized per-scene leading to prohibitive reconstruction time. On the other hand, deep multi-view stereo methods can quickly reconstruct…

Computer Vision and Pattern Recognition · Computer Science 2023-03-17 Qiangeng Xu , Zexiang Xu , Julien Philip , Sai Bi , Zhixin Shu , Kalyan Sunkavalli , Ulrich Neumann

Recent advances in novel view synthesis (NVS) have enabled real-time rendering with 3D Gaussian Splatting (3DGS). However, existing methods struggle with artifacts and missing regions when rendering from viewpoints that deviate from the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Minsu Kim , Subin Jeon , In Cho , Mijin Yoo , Seon Joo Kim

The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the rendering speed of novel view synthesis. Unlike neural implicit representations like Neural Radiance Fields (NeRF) that represent a 3D scene with position and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Tong Wu , Yu-Jie Yuan , Ling-Xiao Zhang , Jie Yang , Yan-Pei Cao , Ling-Qi Yan , Lin Gao