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We introduce a novel method for measuring properties of periodic phenomena with an event camera, a device asynchronously reporting brightness changes at independently operating pixels. The approach assumes that for fast periodic phenomena,…

Computer Vision and Pattern Recognition · Computer Science 2024-02-26 Jakub Kolář , Radim Špetlík , Jiří Matas

Event cameras are novel sensors that report brightness changes in the form of asynchronous "events" instead of intensity frames. They have significant advantages over conventional cameras: high temporal resolution, high dynamic range, and…

Computer Vision and Pattern Recognition · Computer Science 2019-04-18 Henri Rebecq , René Ranftl , Vladlen Koltun , Davide Scaramuzza

We present a novel method for measuring the rate of periodic phenomena (e.g., rotation, flicker, and vibration), by an event camera, a device asynchronously reporting brightness changes at independently operating pixels with high temporal…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Jakub Kolář , Radim Špetlík , Jiří Matas

Most of the artificial lights fluctuate in response to the grid's alternating current and exhibit subtle variations in terms of both intensity and spectrum, providing the potential to estimate the Electric Network Frequency (ENF) from…

Image and Video Processing · Electrical Eng. & Systems 2023-05-05 Lexuan Xu , Guang Hua , Haijian Zhang , Lei Yu , Ning Qiao

Estimating neural radiance fields (NeRFs) from "ideal" images has been extensively studied in the computer vision community. Most approaches assume optimal illumination and slow camera motion. These assumptions are often violated in robotic…

Computer Vision and Pattern Recognition · Computer Science 2023-01-25 Simon Klenk , Lukas Koestler , Davide Scaramuzza , Daniel Cremers

Event cameras or dynamic vision sensors (DVS) record asynchronous response to brightness changes instead of conventional intensity frames, and feature ultra-high sensitivity at low bandwidth. The new mechanism demonstrates great advantages…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Bo Zhang , Yuqi Han , Jinli Suo , Qionghai Dai

Deep learning inference that needs to largely take place on the 'edge' is a highly computational and memory intensive workload, making it intractable for low-power, embedded platforms such as mobile nodes and remote security applications.…

Computer Vision and Pattern Recognition · Computer Science 2020-07-23 Andres Ussa , Chockalingam Senthil Rajen , Deepak Singla , Jyotibdha Acharya , Gideon Fu Chuanrong , Arindam Basu , Bharath Ramesh

Event-based cameras are bio-inspired sensors with pixels that independently and asynchronously respond to brightness changes at microsecond resolution, offering the potential to handle visual tasks in challenging scenarios. However, due to…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Sheng Zhong , Zhongyang Ren , Xiya Zhu , Dehao Yuan , Cornelia Fermuller , Yi Zhou

Scene reconstruction from casually captured videos has wide applications in real-world scenarios. With recent advancements in differentiable rendering techniques, several methods have attempted to simultaneously optimize scene…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Bohao Liao , Wei Zhai , Zengyu Wan , Zhixin Cheng , Wenfei Yang , Tianzhu Zhang , Yang Cao , Zheng-Jun Zha

Traditional frame-based cameras inevitably suffer from motion blur due to long exposure times. As a kind of bio-inspired camera, the event camera records the intensity changes in an asynchronous way with high temporal resolution, providing…

Computer Vision and Pattern Recognition · Computer Science 2023-01-13 Lei Sun , Christos Sakaridis , Jingyun Liang , Qi Jiang , Kailun Yang , Peng Sun , Yaozu Ye , Kaiwei Wang , Luc Van Gool

Event cameras provide asynchronous, data-driven measurements of local temporal contrast over a large dynamic range with extremely high temporal resolution. Conventional cameras capture low-frequency reference intensity information. These…

Computer Vision and Pattern Recognition · Computer Science 2018-11-02 Cedric Scheerlinck , Nick Barnes , Robert Mahony

Visible images offer rich texture details, while infrared images emphasize salient targets. Fusing these complementary modalities enhances scene understanding, particularly for advanced vision tasks under challenging conditions. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Beining Xu , Junxian Li

The growing availability of commodity RGB-D cameras has boosted the applications in the field of scene understanding. However, as a fundamental scene understanding task, surface normal estimation from RGB-D data lacks thorough…

Computer Vision and Pattern Recognition · Computer Science 2019-11-21 Jin Zeng , Yanfeng Tong , Yunmu Huang , Qiong Yan , Wenxiu Sun , Jing Chen , Yongtian Wang

The neuromorphic event cameras, which capture the optical changes of a scene, have drawn increasing attention due to their high speed and low power consumption. However, the event data are noisy, sparse, and nonuniform in the…

Computer Vision and Pattern Recognition · Computer Science 2021-03-23 Chang Liu , Xiaojuan Qi , Edmund Lam , Ngai Wong

Photometric stereo is a powerful method for obtaining per-pixel surface normals from differently illuminated images of an object. While several methods address photometric stereo with different image (or light) counts ranging from one to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Ashish Tiwari , Mihir Sutariya , Shanmuganathan Raman

We focus on a very challenging task: imaging at nighttime dynamic scenes. Most previous methods rely on the low-light enhancement of a conventional RGB camera. However, they would inevitably face a dilemma between the long exposure time of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Haoyue Liu , Shihan Peng , Lin Zhu , Yi Chang , Hanyu Zhou , Luxin Yan

Event cameras have shown promise in vision applications like optical flow estimation and stereo matching, with many specialized architectures leveraging the asynchronous and sparse nature of event data. However, existing works only focus…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Pengjie Zhang , Lin Zhu , Xiao Wang , Lizhi Wang , Wanxuan Lu , Hua Huang

Event cameras sense intensity changes and have many advantages over conventional cameras. To take advantage of event cameras, some methods have been proposed to reconstruct intensity images from event streams. However, the outputs are still…

Computer Vision and Pattern Recognition · Computer Science 2020-03-18 Lin Wang , Tae-Kyun Kim , Kuk-Jin Yoon

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

Detecting and magnifying imperceptible high-frequency motions in real-world scenarios has substantial implications for industrial and medical applications. These motions are characterized by small amplitudes and high frequencies.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Yutian Chen , Shi Guo , Fangzheng Yu , Feng Zhang , Jinwei Gu , Tianfan Xue
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