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Event camera, a novel neuromorphic vision sensor, records data with high temporal resolution and wide dynamic range, offering new possibilities for accurate visual representation in challenging scenarios. However, event data is inherently…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Lin Zhu , Ruonan Liu , Xiao Wang , Lizhi Wang , Hua Huang

Event cameras do not produce images, but rather a continuous flow of events, which encode changes of illumination for each pixel independently and asynchronously. While they output temporally rich information, they lack any depth…

Computer Vision and Pattern Recognition · Computer Science 2023-03-01 Vincent Brebion , Julien Moreau , Franck Davoine

Dynamic Vision Sensor (DVS)-based solutions have recently garnered significant interest across various computer vision tasks, offering notable benefits in terms of dynamic range, temporal resolution, and inference speed. However, as a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Zhongyang Zhang , Shuyang Cui , Kaidong Chai , Haowen Yu , Subhasis Dasgupta , Upal Mahbub , Tauhidur Rahman

The high frame rate is a critical requirement for capturing fast human motions. In this setting, existing markerless image-based methods are constrained by the lighting requirement, the high data bandwidth and the consequent high…

Computer Vision and Pattern Recognition · Computer Science 2019-09-02 Lan Xu , Weipeng Xu , Vladislav Golyanik , Marc Habermann , Lu Fang , Christian Theobalt

Event cameras are dynamic vision sensors inspired by the biological retina, characterized by their high dynamic range, high temporal resolution, and low power consumption. These features make them capable of perceiving 3D environments even…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Hoonhee Cho , Jae-Young Kang , Kuk-Jin Yoon

High dynamic range (HDR) imaging under extreme illumination remains challenging for conventional cameras due to overexposure. Event cameras provide microsecond temporal resolution and high dynamic range, while spatially varying exposure…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Pengju Sun , Banglei Guan , Jing Tao , Zhenbao Yu , Xuanyu Bai , Yang Shang , Qifeng Yu

Video anomaly detection aims to find the events in a video that do not conform to the expected behavior. The prevalent methods mainly detect anomalies by snippet reconstruction or future frame prediction error. However, the error is highly…

Computer Vision and Pattern Recognition · Computer Science 2022-09-08 Congqi Cao , Yue Lu , Yanning Zhang

Event cameras are novel bio-inspired sensors that offer advantages over traditional cameras (low latency, high dynamic range, low power, etc.). Optical flow estimation methods that work on packets of events trade off speed for accuracy,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Shintaro Shiba , Yoshimitsu Aoki , Guillermo Gallego

Event-based cameras are bio-inspired sensors that capture brightness change of every pixel in an asynchronous manner. Compared with frame-based sensors, event cameras have microsecond-level latency and high dynamic range, hence showing…

Computer Vision and Pattern Recognition · Computer Science 2023-03-20 Dongsheng Wang , Xu Jia , Yang Zhang , Xinyu Zhang , Yaoyuan Wang , Ziyang Zhang , Dong Wang , Huchuan Lu

We introduce N-ImageNet, a large-scale dataset targeted for robust, fine-grained object recognition with event cameras. The dataset is collected using programmable hardware in which an event camera consistently moves around a monitor…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Junho Kim , Jaehyeok Bae , Gangin Park , Dongsu Zhang , Young Min Kim

Event cameras offer low-power visual sensing capabilities ideal for edge-device applications. However, their high event rate, driven by high temporal details, can be restrictive in terms of bandwidth and computational resources. In edge AI…

Computer Vision and Pattern Recognition · Computer Science 2024-09-16 Hesam Araghi , Jan van Gemert , Nergis Tomen

Applying image processing algorithms independently to each frame of a video often leads to undesired inconsistent results over time. Developing temporally consistent video-based extensions, however, requires domain knowledge for individual…

Computer Vision and Pattern Recognition · Computer Science 2018-08-02 Wei-Sheng Lai , Jia-Bin Huang , Oliver Wang , Eli Shechtman , Ersin Yumer , Ming-Hsuan Yang

Tracking using bio-inspired event cameras has drawn more and more attention in recent years. Existing works either utilize aligned RGB and event data for accurate tracking or directly learn an event-based tracker. The first category needs…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Xiao Wang , Shiao Wang , Chuanming Tang , Lin Zhu , Bo Jiang , Yonghong Tian , Jin Tang

Event cameras offer a promising avenue for multi-view stereo depth estimation and Simultaneous Localization And Mapping (SLAM) due to their ability to detect blur-free 3D edges at high-speed and over broad illumination conditions. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Diego Hitzges , Suman Ghosh , Guillermo Gallego

Event cameras are sensors inspired by biological systems that specialize in capturing changes in brightness. These emerging cameras offer many advantages over conventional frame-based cameras, including high dynamic range, high frame rates,…

Computer Vision and Pattern Recognition · Computer Science 2023-09-04 Haodong Chen , Vera Chung , Li Tan , Xiaoming Chen

Event cameras capture the world at high time resolution and with minimal bandwidth requirements. However, event streams, which only encode changes in brightness, do not contain sufficient scene information to support a wide variety of…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Varun Sundar , Matthew Dutson , Andrei Ardelean , Claudio Bruschini , Edoardo Charbon , Mohit Gupta

Event cameras, or Dynamic Vision Sensors (DVS) are novel neuromorphic sensors that capture brightness changes as a continuous stream of "events" rather than traditional intensity frames. Converting sparse events to dense intensity frames…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Yuhan Bao , Lei Sun , Yuqin Ma , Kaiwei Wang

Reliable hand mesh reconstruction (HMR) from commonly-used color and depth sensors is challenging especially under scenarios with varied illuminations and fast motions. Event camera is a highly promising alternative for its high dynamic…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Jianping Jiang , Xinyu Zhou , Bingxuan Wang , Xiaoming Deng , Chao Xu , Boxin Shi

Traditionally, video is structured as a sequence of discrete image frames. Recently, however, a novel video sensing paradigm has emerged which eschews video frames entirely. These "event" sensors aim to mimic the human vision system with…

Multimedia · Computer Science 2024-08-13 Andrew Freeman

Event cameras are neuromorphic sensors that capture asynchronous and sparse event stream when per-pixel brightness changes. The state-of-the-art processing methods for event signals typically aggregate events into a frame or a grid.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Beibei Yang , Weiling Li , Yan Fang
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