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Event cameras offer significant advantages for low-light video enhancement, primarily due to their high dynamic range. Current research, however, is severely limited by the absence of large-scale, real-world, and spatio-temporally aligned…

Computer Vision and Pattern Recognition · Computer Science 2024-08-30 Kanghao Chen , Guoqiang Liang , Hangyu Li , Yunfan Lu , Lin Wang

Event cameras are innovative neuromorphic sensors that asynchronously capture the scene dynamics. Due to the event-triggering mechanism, such cameras record event streams with much shorter response latency and higher intensity sensitivity…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Yunhao Zou , Ying Fu , Tsuyoshi Takatani , Yinqiang Zheng

Self-supervised monocular depth estimation (SS-MDE) has the potential to scale to vast quantities of data. Unfortunately, existing approaches limit themselves to the automotive domain, resulting in models incapable of generalizing to…

Computer Vision and Pattern Recognition · Computer Science 2023-07-21 Jaime Spencer , Chris Russell , Simon Hadfield , Richard Bowden

Event-based cameras have shown great promise in a variety of situations where frame based cameras suffer, such as high speed motions and high dynamic range scenes. However, developing algorithms for event measurements requires a new class…

Computer Vision and Pattern Recognition · Computer Science 2018-08-14 Alex Zihao Zhu , Liangzhe Yuan , Kenneth Chaney , Kostas Daniilidis

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

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

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

An event camera is a novel vision sensor that can capture per-pixel brightness changes and output a stream of asynchronous ``events''. It has advantages over conventional cameras in those scenes with high-speed motions and challenging…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Junyu Zhu , Lina Liu , Bofeng Jiang , Feng Wen , Hongbo Zhang , Wanlong Li , Yong Liu

Stereopsis has widespread appeal in robotics as it is the predominant way by which living beings perceive depth to navigate our 3D world. Event cameras are novel bio-inspired sensors that detect per-pixel brightness changes asynchronously,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Suman Ghosh , Guillermo Gallego

Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have a very high dynamic range, which enables them to provide…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Guillermo Gallego , Jon E. A. Lund , Elias Mueggler , Henri Rebecq , Tobi Delbruck , Davide Scaramuzza

The broad scope of obstacle avoidance has led to many kinds of computer vision-based approaches. Despite its popularity, it is not a solved problem. Traditional computer vision techniques using cameras and depth sensors often focus on…

Computer Vision and Pattern Recognition · Computer Science 2022-12-06 Celyn Walters , Simon Hadfield

Event cameras are novel sensors that output brightness changes in the form of a stream of asynchronous "events" instead of intensity frames. They offer significant advantages with respect to conventional cameras: high dynamic range (HDR),…

Computer Vision and Pattern Recognition · Computer Science 2020-04-02 Daniel Gehrig , Mathias Gehrig , Javier Hidalgo-Carrió , Davide Scaramuzza

Event cameras offer superior sensitivity to high-speed motion and extreme lighting, making event-based monocular depth estimation a promising approach for robust 3D perception in challenging conditions. However, progress is severely…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Yinrui Ren , Jinjing Zhu , Kanghao Chen , Zhuoxiao Li , Jing Ou , Zidong Cao , Tongyan Hua , Peilun Shi , Yingchun Fu , Wufan Zhao , Hui Xiong

In recent decades, visual simultaneous localization and mapping (vSLAM) has gained significant interest in both academia and industry. It estimates camera motion and reconstructs the environment concurrently using visual sensors on a moving…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Kunping Huang , Sen Zhang , Jing Zhang , Dacheng Tao

Real-time understanding of long video streams remains challenging for multimodal large language models (VLMs) due to redundant frame processing and rapid forgetting of past context. Existing streaming systems rely on fixed-interval decoding…

Computer Vision and Pattern Recognition · Computer Science 2026-01-23 Zhenghui Guo , Yuanbin Man , Junyuan Sheng , Bowen Lin , Ahmed Ahmed , Bo Jiang , Boyuan Zhang , Miao Yin , Sian Jin , Omprakash Gnawal , Chengming Zhang

This paper presents Ev-Layout, a novel large-scale event-based multi-modal dataset designed for indoor layout estimation and tracking. Ev-Layout makes key contributions to the community by: Utilizing a hybrid data collection platform (with…

Graphics · Computer Science 2025-03-12 Xucheng Guo , Yiran Shen , Xiaofang Xiao , Yuanfeng Zhou , Lin Wang

Event cameras respond to changes in log-brightness at the millisecond level, making them ideal for optical flow estimation. However, existing datasets from event cameras provide only low frame rate ground truth for optical flow, limiting…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Yaozu Ye , Hao Shi , Kailun Yang , Ze Wang , Xiaoting Yin , Lei Sun , Yaonan Wang , Kaiwei Wang

Dynamic Vision Sensors (DVS) capture event data with high temporal resolution and low power consumption, presenting a more efficient solution for visual processing in dynamic and real-time scenarios compared to conventional video capture…

Computer Vision and Pattern Recognition · Computer Science 2025-02-14 Yiting Dong , Xiang He , Guobin Shen , Dongcheng Zhao , Yang Li , Yi Zeng

Event cameras encode visual information with high temporal precision, low data-rate, and high-dynamic range. Thanks to these characteristics, event cameras are particularly suited for scenarios with high motion, challenging lighting…

Computer Vision and Pattern Recognition · Computer Science 2020-12-10 Etienne Perot , Pierre de Tournemire , Davide Nitti , Jonathan Masci , Amos Sironi

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
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