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Event cameras are vision sensors that record asynchronous streams of per-pixel brightness changes, referred to as "events". They have appealing advantages over frame-based cameras for computer vision, including high temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-21 Daniel Gehrig , Antonio Loquercio , Konstantinos G. Derpanis , Davide Scaramuzza

Light field microscopy (LFM) has gained significant attention due to its ability to capture snapshot-based, large-scale 3D fluorescence images. However, existing LFM reconstruction algorithms are highly sensitive to sensor noise or require…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Jiayin Zhao , Zhenqi Fu , Tao Yu , Hui Qiao

High-speed imaging is central to the experimental investigation of fast phenomena, like flapping flags. Event-based cameras use new types of sensors that address typical challenges such as low illumination conditions, large data transfer,…

Fluid Dynamics · Physics 2024-12-10 Gaetan Raynaud , Karen Mulleners

We tackle the problem of automatically reconstructing a complete 3D model of a scene from a single RGB image. This challenging task requires inferring the shape of both visible and occluded surfaces. Our approach utilizes viewer-centered,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-28 Daeyun Shin , Zhile Ren , Erik B. Sudderth , Charless C. Fowlkes

Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of "events". The innovative way they acquire data presents several advantages over standard devices, especially in poor…

Computer Vision and Pattern Recognition · Computer Science 2021-11-01 Mirco Planamente , Chiara Plizzari , Marco Cannici , Marco Ciccone , Francesco Strada , Andrea Bottino , Matteo Matteucci , Barbara Caputo

We present a new hierarchical compression scheme for encoding light field images (LFI) that is suitable for interactive rendering. Our method (RLFC) exploits redundancies in the light field images by constructing a tree structure. The top…

Graphics · Computer Science 2019-03-01 Srihari Pratapa , Dinesh Manocha

A new method for dark field imaging is introduced which uses scanned electron diffraction (or 4DSTEM - 4-dimensional scanning transmission electron microscopy) datasets as its input. Instead of working on simple summation of intensity, it…

Materials Science · Physics 2024-09-18 Ian MacLaren , Andrew T. Fraser , Matthew R. Lipsett , Colin Ophus

Visual object tracking under challenging conditions of motion and light can be hindered by the capabilities of conventional cameras, prone to producing images with motion blur. Event cameras are novel sensors suited to robustly perform…

Computer Vision and Pattern Recognition · Computer Science 2022-12-16 Irene Perez-Salesa , Rodrigo Aldana-Lopez , Carlos Sagues

Low-light video enhancement (LLVE) is an important yet challenging task with many applications such as photographing and autonomous driving. Unlike single image low-light enhancement, most LLVE methods utilize temporal information from…

Computer Vision and Pattern Recognition · Computer Science 2022-08-24 Lin Liu , Junfeng An , Jianzhuang Liu , Shanxin Yuan , Xiangyu Chen , Wengang Zhou , Houqiang Li , Yanfeng Wang , Qi Tian

Light field data records the amount of light at multiple points in space, captured e.g. by an array of cameras or by a light-field camera that uses microlenses. Since the storage and transmission requirements for such data are tremendous,…

Image and Video Processing · Electrical Eng. & Systems 2019-05-21 David Barina , Tomas Chlubna , Marek Solony , Drahomir Dlabaja , Pavel Zemcik

Neural Radiance Fields (NeRF) achieves impressive 3D representation learning and novel view synthesis results with high-quality multi-view images as input. However, motion blur in images often occurs in low-light and high-speed motion…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Yunshan Qi , Lin Zhu , Yifan Zhao , Nan Bao , Jia Li

Event cameras, which are asynchronous bio-inspired vision sensors, have shown great potential in computer vision and artificial intelligence. However, the application of event cameras to object-level motion estimation or tracking is still…

Computer Vision and Pattern Recognition · Computer Science 2020-09-21 Haosheng Chen , David Suter , Qiangqiang Wu , Hanzi Wang

Recovering sharp video sequence from a motion-blurred image is highly ill-posed due to the significant loss of motion information in the blurring process. For event-based cameras, however, fast motion can be captured as events at high time…

Computer Vision and Pattern Recognition · Computer Science 2020-04-14 Zhe Jiang , Yu Zhang , Dongqing Zou , Jimmy Ren , Jiancheng Lv , Yebin Liu

Pose estimation and tracking of objects is a fundamental application in 3D vision. Event cameras possess remarkable attributes such as high dynamic range, low latency, and resilience against motion blur, which enables them to address…

Computer Vision and Pattern Recognition · Computer Science 2024-08-07 Zibin Liu , Banglei Guan , Yang Shang , Qifeng Yu , Laurent Kneip

Contrary to conventional frame-based imaging, event-based vision (EBV) or dynamic vision sensing (DVS) asynchronously records binary signals of intensity changes for given pixels with microsecond resolution. The present work explores the…

Fluid Dynamics · Physics 2022-06-22 Christian Willert , Joachim Klinner

Under extreme low-light conditions, frame-based cameras suffer from severe detail loss due to limited dynamic range. Recent studies have introduced event cameras for event-guided low-light image enhancement. However, existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Zhanwen Liu , Huanna Song , Yang Wang , Nan Yang , Weiping Ding , Yisheng An

Event cameras provide microsecond latency, making them suitable for 6D object pose tracking in fast, dynamic scenes where conventional RGB and depth pipelines suffer from motion blur and large pixel displacements. We introduce EventTrack6D,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Jae-Young Kang , Hoonhee Cho , Taeyeop Lee , Minjun Kang , Bowen Wen , Youngho Kim , Kuk-Jin Yoon

This paper explores the problem of reconstructing high-resolution light field (LF) images from hybrid lenses, including a high-resolution camera surrounded by multiple low-resolution cameras. To tackle this challenge, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2020-08-04 Jing Jin , Junhui Hou , Jie Chen , Sam Kwong , Jingyi Yu

Event cameras output asynchronous events to represent intensity changes with a high temporal resolution, even under extreme lighting conditions. Currently, most of the existing works use a single contrast threshold to estimate the intensity…

Computer Vision and Pattern Recognition · Computer Science 2020-12-18 Ziwei Wang , Yonhon Ng , Pieter van Goor , Robert Mahony

Line segment extraction is effective for capturing geometric features of human-made environments. Event-based cameras, which asynchronously respond to contrast changes along edges, enable efficient extraction by reducing redundant data.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-09 Mikihiro Ikura , Arren Glover , Masayoshi Mizuno , Chiara Bartolozzi