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Event cameras are a new type of brain-inspired visual sensor with advantages such as high dynamic range and high temporal resolution. The geometric calibration of event cameras, which involves determining their intrinsic and extrinsic…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Zibin Liu , Shunkun Liang , Banglei Guan , Dongcai Tan , Yang Shang , Qifeng Yu

Event camera sensors are bio-inspired sensors which asynchronously capture per-pixel brightness changes and output a stream of events encoding the polarity, location and time of these changes. These systems are witnessing rapid advancements…

Computer Vision and Pattern Recognition · Computer Science 2025-09-15 Aupendu Kar , Vishnu Raj , Guan-Ming Su

Human pose estimation is critical for applications such as rehabilitation, sports analytics, and AR/VR systems. However, rapid motion and low-light conditions often introduce motion blur, significantly degrading pose estimation due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Youngho Kim , Hoonhee Cho , Kuk-Jin Yoon

Moving Object Detection (MOD) is a critical vision task for successfully achieving safe autonomous driving. Despite plausible results of deep learning methods, most existing approaches are only frame-based and may fail to reach reasonable…

Computer Vision and Pattern Recognition · Computer Science 2023-03-10 Zhuyun Zhou , Zongwei Wu , Rémi Boutteau , Fan Yang , Cédric Demonceaux , Dominique Ginhac

Event-based vision, inspired by the human visual system, offers transformative capabilities such as low latency, high dynamic range, and reduced power consumption. This paper presents a comprehensive survey of event cameras, tracing their…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Bharatesh Chakravarthi , Aayush Atul Verma , Kostas Daniilidis , Cornelia Fermuller , Yezhou Yang

Event cameras provide high temporal resolution, high dynamic range, and low latency, offering significant advantages over conventional frame-based cameras. In this work, we introduce an uncertainty-aware refinement network called URNet for…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Yifeng Cheng , Alois Knoll , Hu Cao

Implicit neural representation and explicit 3D Gaussian Splatting (3D-GS) for novel view synthesis have achieved remarkable progress with frame-based camera (e.g. RGB and RGB-D cameras) recently. Compared to frame-based camera, a novel type…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Jian Huang , Chengrui Dong , Xuanhua Chen , Peidong Liu

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

Tracking Any Point (TAP) plays a crucial role in motion analysis. Video-based approaches rely on iterative local matching for tracking, but they assume linear motion during the blind time between frames, which leads to point loss under…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Han Han , Wei Zhai , Yang Cao , Bin Li , Zheng-jun Zha

We tackle the problem of bundle adjustment (i.e., simultaneous refinement of camera poses and scene map) for a purely rotating event camera. Starting from first principles, we formulate the problem as a classical non-linear least squares…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Shuang Guo , Guillermo Gallego

Event Cameras, also known as Neuromorphic sensors, capture changes in local light intensity at the pixel level, producing asynchronously generated data termed ``events''. This distinct data format mitigates common issues observed in…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Khadija Iddrisu , Waseem Shariff , Noel E. OConnor , Joseph Lemley , Suzanne Little

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

In this work, we introduce the first framework for Motion-aware Event Suppression, which learns to filter events triggered by IMOs and ego-motion in real time. Our model jointly segments IMOs in the current event stream while predicting…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Roberto Pellerito , Nico Messikommer , Giovanni Cioffi , Marco Cannici , Davide Scaramuzza

Augmented reality devices require multiple sensors to perform various tasks such as localization and tracking. Currently, popular cameras are mostly frame-based (e.g. RGB and Depth) which impose a high data bandwidth and power usage. With…

Computer Vision and Pattern Recognition · Computer Science 2020-08-07 Etienne Dubeau , Mathieu Garon , Benoit Debaque , Raoul de Charette , Jean-François Lalonde

Face analysis has been studied from different angles to infer emotion, poses, shapes, and landmarks. Traditionally RGB cameras are used, yet for fine-grained tasks standard sensors might not be up to the task due to their latency, making it…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Luca Cultrera , Federico Becattini , Lorenzo Berlincioni , Claudio Ferrari , Alberto Del Bimbo

Visible images have been widely used for motion estimation. Thermal images, in contrast, are more challenging to be used in motion estimation since they typically have lower resolution, less texture, and more noise. In this paper, a novel…

Computer Vision and Pattern Recognition · Computer Science 2021-05-18 Weichen Dai , Yu Zhang , Shenzhou Chen , Donglei Sun , Da Kong

This work presents a novel RGB-D-inertial dynamic SLAM method that can enable accurate localisation when the majority of the camera view is occluded by multiple dynamic objects over a long period of time. Most dynamic SLAM approaches either…

Robotics · Computer Science 2023-03-24 Ran Long , Christian Rauch , Vladimir Ivan , Tin Lun Lam , Sethu Vijayakumar

Background: Large engineering structures, such as space launch towers and suspension bridges, are subjected to extreme forces that cause high-speed 3D deformation and compromise safety. These structures typically operate under extreme…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Banglei Guan , Yifei Bian , Zibin Liu , Haoyang Li , Xuanyu Bai , Taihang Lei , Bin Li , Yang Shang , Qifeng Yu

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

Real-time object pose estimation and tracking is challenging but essential for emerging augmented reality (AR) applications. In general, state-of-the-art methods address this problem using deep neural networks which indeed yield…

Computer Vision and Pattern Recognition · Computer Science 2023-12-13 Yo-Chung Lau , Kuan-Wei Tseng , I-Ju Hsieh , Hsiao-Ching Tseng , Yi-Ping Hung
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