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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 are bio-inspired cameras which can measure the change of intensity asynchronously with high temporal resolution. One of the event cameras' advantages is that they do not suffer from motion blur when recording high-speed…

Computer Vision and Pattern Recognition · Computer Science 2020-03-23 Chen Haoyu , Teng Minggui , Shi Boxin , Wang YIzhou , Huang Tiejun

Event cameras such as DAVIS can simultaneously output high temporal resolution events and low frame-rate intensity images, which own great potential in capturing scene motion, such as optical flow estimation. Most of the existing optical…

Computer Vision and Pattern Recognition · Computer Science 2022-11-18 Zhexiong Wan , Yuchao Dai , Yuxin Mao

The bio-inspired event cameras or dynamic vision sensors are capable of asynchronously capturing per-pixel brightness changes (called event-streams) in high temporal resolution and high dynamic range. However, the non-structural…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Qiang Qu , Yiran Shen , Xiaoming Chen , Yuk Ying Chung , Tongliang Liu

Event cameras are a bio-inspired class of sensors that asynchronously measure per-pixel intensity changes. Under fixed illumination conditions in static or low-motion scenes, rigidly mounted event cameras are unable to generate any events…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Vincenzo Polizzi , Stephen Yang , Quentin Clark , Jonathan Kelly , Igor Gilitschenski , David B. Lindell

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

Event cameras respond to brightness changes in the scene asynchronously and independently for every pixel. Due to the properties, these cameras have distinct features: high dynamic range (HDR), high temporal resolution, and low power…

Computer Vision and Pattern Recognition · Computer Science 2022-10-17 Jongwan Kim , DongJin Lee , Byunggook Na , Seongsik Park , Jeonghee Jo , Sungroh Yoon

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

We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image and an event camera stream. Conventional cameras struggle with high-speed motion capture due to bandwidth and dynamic range…

Computer Vision and Pattern Recognition · Computer Science 2025-04-25 Ziyun Wang , Friedhelm Hamann , Kenneth Chaney , Wen Jiang , Guillermo Gallego , Kostas Daniilidis

Slow shutter speed and long exposure time of frame-based cameras often cause visual blur and loss of inter-frame information, degenerating the overall quality of captured videos. To this end, we present a unified framework of event-based…

Computer Vision and Pattern Recognition · Computer Science 2022-04-15 Xiang Zhang , Lei Yu

Event cameras are ideally suited to capture HDR visual information without blur but perform poorly on static or slowly changing scenes. Conversely, conventional image sensors measure absolute intensity of slowly changing scenes effectively…

Computer Vision and Pattern Recognition · Computer Science 2022-05-12 Ziwei Wang , Yonhon Ng , Cedric Scheerlinck , Robert Mahony

High dynamic range imaging (HDRI) for real-world dynamic scenes is challenging because moving objects may lead to hybrid degradation of low dynamic range and motion blur. Existing event-based approaches only focus on a separate task, while…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Li Xiaopeng , Zeng Zhaoyuan , Fan Cien , Zhao Chen , Deng Lei , Yu Lei

Event cameras are bio-inspired, motion-activated sensors that demonstrate substantial potential in handling challenging situations, such as motion blur and high-dynamic range. In this paper, we proposed EVI-SAM to tackle the problem of 6…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Weipeng Guan , Peiyu Chen , Huibin Zhao , Yu Wang , Peng Lu

Event cameras, mimicking the human retina, capture brightness changes with unparalleled temporal resolution and dynamic range. Integrating events into intensities poses a highly ill-posed challenge, marred by initial condition ambiguities.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Jinxiu Liang , Bohan Yu , Yixin Yang , Yiming Han , Boxin Shi

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

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

With extremely high temporal resolution, event cameras have a large potential for robotics and computer vision. However, their asynchronous imaging mechanism often aggravates the measurement sensitivity to noises and brings a physical…

Computer Vision and Pattern Recognition · Computer Science 2020-07-17 Bishan Wang , Jingwei He , Lei Yu , Gui-Song Xia , Wen Yang

Event cameras have a lot of advantages over traditional cameras, such as low latency, high temporal resolution, and high dynamic range. However, since the outputs of event cameras are the sequences of asynchronous events overtime rather…

Computer Vision and Pattern Recognition · Computer Science 2020-10-13 S. Mohammad Mostafavi I. , Lin Wang , Yo-Sung Ho , Kuk-Jin Yoon

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

Slow motion videos are becoming increasingly popular, but capturing high-resolution videos at extremely high frame rates requires professional high-speed cameras. To mitigate this problem, current techniques increase the frame rate of…

Computer Vision and Pattern Recognition · Computer Science 2020-04-22 Avinash Paliwal , Nima Khademi Kalantari