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Event cameras asynchronously capture brightness changes with microsecond latency, offering exceptional temporal precision but suffering from severe noise and signal inconsistencies. Unlike conventional signals, events carry state…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Jinze Chen , Wei Zhai , Yang Cao , Bin Li , Zheng-Jun Zha

Dynamic Vision Sensors (DVSs) asynchronously stream events in correspondence of pixels subject to brightness changes. Differently from classic vision devices, they produce a sparse representation of the scene. Therefore, to apply standard…

Computer Vision and Pattern Recognition · Computer Science 2020-08-03 Marco Cannici , Marco Ciccone , Andrea Romanoni , Matteo Matteucci

Event cameras output event streams as sparse, asynchronous data with microsecond-level temporal resolution, enabling visual perception with low latency and a high dynamic range. While existing Multimodal Large Language Models (MLLMs) have…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Rui Chen , Xingyu Chen , Shaoan Wang , Shihan Kong , Junzhi Yu

Previous studies on event camera sensing have demonstrated certain detection performance using dense event representations. However, the accumulated noise in such dense representations has received insufficient attention, which degrades the…

Robotics · Computer Science 2025-06-12 Yangjie Cui , Boyang Gao , Yiwei Zhang , Xin Dong , Jinwu Xiang , Daochun Li , Zhan Tu

Object detection and tracking is an essential perception task for enabling fully autonomous navigation in robotic systems. Edge robot systems such as small drones need to execute complex maneuvers at high-speeds with limited resources,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Adarsh Kumar Kosta , Amogh Joshi , Arjun Roy , Rohan Kumar Manna , Manish Nagaraj , Kaushik Roy

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

Inspired by frame-based methods, state-of-the-art event-based optical flow networks rely on the explicit construction of correlation volumes, which are expensive to compute and store, rendering them unsuitable for robotic applications with…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Yilun Wu , Federico Paredes-Vallés , Guido C. H. E. de Croon

Gait recognition enables non-intrusive, privacy-preserving identification but suffers in uncontrolled environments due to illumination and motion sensitivity of conventional cameras. In this work, we explore gait recognition using event…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Senyan Xu , Shuai Chen , Chuanfu Shen , Kean Liu , Zhijing Sun , Chengzhi Cao , Xueyang Fu

Event-based multimodal large language models (MLLMs) enable robust perception in high-speed and low-light scenarios, addressing key limitations of frame-based MLLMs. However, current event-based MLLMs often rely on dense image-like…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Shaoyu Liu , Jianing Li , Guanghui Zhao , Yunjian Zhang , Wen Jiang , Ming Li , Xiangyang Ji

Real-time object detection takes an essential part in the decision-making process of numerous real-world applications, including collision avoidance and path planning in autonomous driving systems. This paper presents a novel real-time…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Xiang Zhang , Chenchen Fu , Yufei Cui , Lan Yi , Yuyang Sun , Weiwei Wu , Xue Liu

Event-based cameras asynchronously capture individual visual changes in a scene. This makes them more robust than traditional frame-based cameras to highly dynamic motions and poor illumination. It also means that every measurement in a…

Robotics · Computer Science 2023-09-14 Jianeng Wang , Jonathan D. Gammell

Quadrupedal robots are conquering various indoor and outdoor applications due to their ability to navigate challenging uneven terrains. Exteroceptive information greatly enhances this capability since perceiving their surroundings allows…

Robotics · Computer Science 2023-04-07 Benedek Forrai , Takahiro Miki , Daniel Gehrig , Marco Hutter , Davide Scaramuzza

Event cameras are bio-inspired sensors that perform well in HDR conditions and have high temporal resolution. However, different from traditional frame-based cameras, event cameras measure asynchronous pixel-level brightness changes and…

Computer Vision and Pattern Recognition · Computer Science 2022-03-09 Xin Peng , Yifu Wang , Ling Gao , Laurent Kneip

Event-based cameras are dynamic vision sensors that provide asynchronous measurements of changes in per-pixel brightness at a microsecond level. This makes them significantly faster than conventional frame-based cameras, and an appealing…

Computer Vision and Pattern Recognition · Computer Science 2021-10-01 Sai Vemprala , Sami Mian , Ashish Kapoor

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

Recent advances in multimodal foundation models unifying image understanding and generation have opened exciting avenues for tackling a wide range of vision-language tasks within a single framework. Despite progress, existing unified models…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Ying Shen , Zhiyang Xu , Jiuhai Chen , Shizhe Diao , Jiaxin Zhang , Yuguang Yao , Joy Rimchala , Ismini Lourentzou , Lifu Huang

Visual 3D motion estimation aims to infer the motion of 2D pixels in 3D space based on visual cues. The key challenge arises from depth variation induced spatio-temporal motion inconsistencies, disrupting the assumptions of local spatial or…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Zengyu Wan , Wei Zhai , Yang Cao , Zhengjun Zha

This paper investigates trajectory prediction for robotics, to improve the interaction of robots with moving targets, such as catching a bouncing ball. Unexpected, highly-non-linear trajectories cannot easily be predicted with…

Computer Vision and Pattern Recognition · Computer Science 2020-01-16 Marco Monforte , Ander Arriandiaga , Arren Glover , Chiara Bartolozzi

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

The challenge of graphically rendering high frame-rate videos on low compute devices can be addressed through periodic prediction of future frames to enhance the user experience in virtual reality applications. This is studied through the…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Nagabhushan Somraj , Pranali Sancheti , Rajiv Soundararajan
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