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Event cameras are bio-inspired sensors that capture the per-pixel intensity changes asynchronously and produce event streams encoding the time, pixel position, and polarity (sign) of the intensity changes. Event cameras possess a myriad of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-12 Xu Zheng , Yexin Liu , Yunfan Lu , Tongyan Hua , Tianbo Pan , Weiming Zhang , Dacheng Tao , Lin Wang

Event cameras have the ability to capture asynchronous per-pixel brightness changes, called "events", offering advantages over traditional frame-based cameras for computer vision applications. Efficiently coding event data is critical for…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Abdelrahman Seleem , André F. R. Guarda , Nuno M. M. Rodrigues , Fernando Pereira

This paper presents a new method for 3D depth estimation using the output of an asynchronous time driven image sensor. In association with a high speed Digital Light Processing projection system, our method achieves real-time reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2018-11-28 T. Leroux , S. -H. Ieng , R. Benosman

Light field photography has been studied thoroughly in recent years. One of its drawbacks is the need for multi-lens in the imaging. To compensate that, compressed light field photography has been proposed to tackle the trade-offs between…

Computer Vision and Pattern Recognition · Computer Science 2019-02-22 Ofir Nabati , David Mendlovic , Raja Giryes

Light field (LF) imaging, which captures both spatial and angular information of a scene, is undoubtedly beneficial to numerous applications. Although various techniques have been proposed for LF acquisition, achieving both angularly and…

Computer Vision and Pattern Recognition · Computer Science 2022-01-05 Trung-Hieu Tran , Jan Berberich , Sven Simon

Light field (LF) imaging has gained significant attention due to its recent success in 3-dimensional (3D) displaying and rendering as well as augmented and virtual reality usage. Nonetheless, because of the two extra dimensions, LFs are…

Image and Video Processing · Electrical Eng. & Systems 2022-04-20 Eisa Hedayati , Timothy C. Havens , Jeremy P. Bos

Depth of field is an important factor of imaging systems that highly affects the quality of the acquired spatial information. Extended depth of field (EDoF) imaging is a challenging ill-posed problem and has been extensively addressed in…

Image and Video Processing · Electrical Eng. & Systems 2020-05-27 Ugur Akpinar , Erdem Sahin , Monjurul Meem , Rajesh Menon , Atanas Gotchev

We present a method to automatically decompose a light field into its intrinsic shading and albedo components. Contrary to previous work targeted to 2D single images and videos, a light field is a 4D structure that captures non-integrated…

Computer Vision and Pattern Recognition · Computer Science 2017-04-13 Elena Garces , Jose I. Echevarria , Wen Zhang , Hongzhi Wu , Kun Zhou , Diego Gutierrez

Event cameras are rapidly emerging as powerful vision sensors for 3D reconstruction, uniquely capable of asynchronously capturing per-pixel brightness changes. Compared to traditional frame-based cameras, event cameras produce sparse yet…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Chuanzhi Xu , Haoxian Zhou , Langyi Chen , Haodong Chen , Zeke Zexi Hu , Zhicheng Lu , Ying Zhou , Vera Chung , Qiang Qu , Weidong Cai

Event-based structured light systems have recently been introduced as an exciting alternative to conventional frame-based triangulation systems for the 3D measurements of diffuse surfaces. Important benefits include the fast capture speed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Aniket Dashpute , Jiazhang Wang , James Taylor , Oliver Cossairt , Ashok Veeraraghavan , Florian Willomitzer

Light field (LF) image super-resolution (SR) aims at reconstructing high-resolution LF images from their low-resolution counterparts. Although CNN-based methods have achieved remarkable performance in LF image SR, these methods cannot fully…

Computer Vision and Pattern Recognition · Computer Science 2022-01-31 Zhengyu Liang , Yingqian Wang , Longguang Wang , Jungang Yang , Shilin Zhou

Light field (LF) cameras record both intensity and directions of light rays, and encode 3D scenes into 4D LF images. Recently, many convolutional neural networks (CNNs) have been proposed for various LF image processing tasks. However, it…

Image and Video Processing · Electrical Eng. & Systems 2023-07-25 Yingqian Wang , Longguang Wang , Gaochang Wu , Jungang Yang , Wei An , Jingyi Yu , Yulan Guo

In low-light conditions, capturing videos with frame-based cameras often requires long exposure times, resulting in motion blur and reduced visibility. While frame-based motion deblurring and low-light enhancement have been studied, they…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Taewoo Kim , Jaeseok Jeong , Hoonhee Cho , Yuhwan Jeong , Kuk-Jin Yoon

As neuromorphic technology is maturing, its application to robotics and autonomous vehicle systems has become an area of active research. In particular, event cameras have emerged as a compelling alternative to frame-based cameras in…

Computer Vision and Pattern Recognition · Computer Science 2023-02-22 Kevin Ta , David Bruggemann , Tim Brödermann , Christos Sakaridis , Luc Van Gool

In this article we develop an image based rendering technique based on light field reconstruction from a limited set of perspective views acquired by cameras. Our approach utilizes sparse representation of epipolar-plane images in a…

Computer Vision and Pattern Recognition · Computer Science 2015-10-01 Suren Vagharshakyan , Robert Bregovic , Atanas Gotchev

3D shape reconstruction is a primary component of augmented/virtual reality. Despite being highly advanced, existing solutions based on RGB, RGB-D and Lidar sensors are power and data intensive, which introduces challenges for deployment in…

Computer Vision and Pattern Recognition · Computer Science 2020-12-11 Alexis Baudron , Zihao W. Wang , Oliver Cossairt , Aggelos K. Katsaggelos

Low-light image enhancement aims to restore the under-exposure image captured in dark scenarios. Under such scenarios, traditional frame-based cameras may fail to capture the structure and color information due to the exposure time…

Computer Vision and Pattern Recognition · Computer Science 2025-03-05 Xuejian Guo , Zhiqiang Tian , Yuehang Wang , Siqi Li , Yu Jiang , Shaoyi Du , Yue Gao

We present a method for reconstructing a clear Neural Radiance Field (NeRF) even with fast camera motions. To address blur artifacts, we leverage both (blurry) RGB images and event camera data captured in a binocular configuration.…

Computer Vision and Pattern Recognition · Computer Science 2024-09-11 Wei Zhi Tang , Daniel Rebain , Kostantinos G. Derpanis , Kwang Moo Yi

Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological processes. Conventional scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth product (SBP). Emerging…

In low-light environments, conventional cameras often struggle to capture clear multi-view images of objects due to dynamic range limitations and motion blur caused by long exposure. Event cameras, with their high-dynamic range and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Jingqian Wu , Peiqi Duan , Zongqiang Wang , Changwei Wang , Boxin Shi , Edmund Y. Lam