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Dynamic vision sensors or event cameras provide rich complementary information for video frame interpolation. Existing state-of-the-art methods follow the paradigm of combining both synthesis-based and warping networks. However, few of…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Jiaben Chen , Yichen Zhu , Dongze Lian , Jiaqi Yang , Yifu Wang , Renrui Zhang , Xinhang Liu , Shenhan Qian , Laurent Kneip , Shenghua Gao

Novel view synthesis and 4D reconstruction techniques predominantly rely on RGB cameras, thereby inheriting inherent limitations such as the dependence on adequate lighting, susceptibility to motion blur, and a limited dynamic range. Event…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Chaoran Feng , Zhenyu Tang , Wangbo Yu , Yatian Pang , Yian Zhao , Jianbin Zhao , Li Yuan , Yonghong Tian

Given a text query, partially relevant video retrieval (PRVR) aims to retrieve untrimmed videos containing relevant moments, wherein event modeling is crucial for partitioning the video into smaller temporal events that partially correspond…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Sa Zhu , Huashan Chen , Wanqian Zhang , Jinchao Zhang , Zexian Yang , Xiaoshuai Hao , Bo Li

The proliferation of AI-generated content and sophisticated video editing tools has made it both important and challenging to moderate digital platforms. Video watermarking addresses these challenges by embedding imperceptible signals into…

Multimedia · Computer Science 2024-12-13 Pierre Fernandez , Hady Elsahar , I. Zeki Yalniz , Alexandre Mourachko

Event cameras, or Dynamic Vision Sensor (DVS), are very promising sensors which have shown several advantages over frame based cameras. However, most recent work on real applications of these cameras is focused on 3D reconstruction and…

Computer Vision and Pattern Recognition · Computer Science 2019-07-10 Iñigo Alonso , Ana C. Murillo

State-of-the-art frame interpolation methods generate intermediate frames by inferring object motions in the image from consecutive key-frames. In the absence of additional information, first-order approximations, i.e. optical flow, must be…

Computer Vision and Pattern Recognition · Computer Science 2021-06-15 Stepan Tulyakov , Daniel Gehrig , Stamatios Georgoulis , Julius Erbach , Mathias Gehrig , Yuanyou Li , Davide Scaramuzza

Event cameras are paradigm-shifting novel sensors that report asynchronous, per-pixel brightness changes called 'events' with unparalleled low latency. This makes them ideal for high speed, high dynamic range scenes where conventional…

Computer Vision and Pattern Recognition · Computer Science 2020-08-25 Timo Stoffregen , Cedric Scheerlinck , Davide Scaramuzza , Tom Drummond , Nick Barnes , Lindsay Kleeman , Robert Mahony

Small vibrations observed in video can unveil information beyond what is visual, such as sound and material properties. It is possible to passively record these vibrations when they are visually perceptible, or actively amplify their visual…

Image and Video Processing · Electrical Eng. & Systems 2026-01-21 Mingxuan Cai , Dekel Galor , Amit Pal Singh Kohli , Jacob L. Yates , Laura Waller

Event cameras operate fundamentally differently from traditional Active Pixel Sensor (APS) cameras, offering significant advantages. Recent research has developed simulators to convert video frames into events, addressing the shortage of…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Xiao Jiang , Fei Zhou , Jiongzhi Lin

Event cameras have shown promise in vision applications like optical flow estimation and stereo matching, with many specialized architectures leveraging the asynchronous and sparse nature of event data. However, existing works only focus…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Pengjie Zhang , Lin Zhu , Xiao Wang , Lizhi Wang , Wanxuan Lu , Hua Huang

Event cameras deliver visual data with high temporal resolution, low latency, and minimal redundancy, yet their asynchronous, sparse sequential nature challenges standard tensor-based machine learning (ML). While the recent…

Machine Learning · Computer Science 2026-03-09 Haiqing Hao , Nikola Zubić , Weihua He , Zhipeng Sui , Davide Scaramuzza , Wenhui Wang

Recognizing and comprehending human actions and gestures is a crucial perception requirement for robots to interact with humans and carry out tasks in diverse domains, including service robotics, healthcare, and manufacturing. Event…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Tristan de Blegiers , Ishan Rajendrakumar Dave , Adeel Yousaf , Mubarak Shah

Event cameras are novel sensors that perceive the per-pixel intensity changes and output asynchronous event streams with high dynamic range and less motion blur. It has been shown that events alone can be used for end-task learning, e.g.,…

Computer Vision and Pattern Recognition · Computer Science 2021-11-25 Lin Wang , Yujeong Chae , Kuk-Jin Yoon

Most existing video anomaly detectors rely solely on RGB frames, which lack the temporal resolution needed to capture abrupt or transient motion cues, key indicators of anomalous events. To address this limitation, we propose Image-Event…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Sungheon Jeong , Jihong Park , Mohsen Imani

Compared to frame-based methods, computational neuromorphic imaging using event cameras offers significant advantages, such as minimal motion blur, enhanced temporal resolution, and high dynamic range. The multi-view consistency of Neural…

Computer Vision and Pattern Recognition · Computer Science 2025-01-08 Chaoran Feng , Wangbo Yu , Xinhua Cheng , Zhenyu Tang , Junwu Zhang , Li Yuan , Yonghong Tian

Evaluation is essential in image fusion research, yet most existing metrics are directly borrowed from other vision tasks without proper adaptation. These traditional metrics, often based on complex image transformations, not only fail to…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Chunyang Cheng , Tianyang Xu , Xiao-Jun Wu , Tao Zhou , Hui Li , Zhangyong Tang , Josef Kittler

Integrating event cameras with Multimodal Large Language Models (MLLMs) promises general scene understanding in challenging visual conditions, yet requires navigating a trade-off between preserving the unique advantages of event data and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Hanyue Lou , Jiayi Zhou , Yang Zhang , Boyu Li , Yi Wang , Guangnan Ye , Boxin Shi

Event cameras offer various advantages for novel view rendering compared to synchronously operating RGB cameras, and efficient event-based techniques supporting rigid scenes have been recently demonstrated in the literature. In the case of…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Takuya Nakabayashi , Navami Kairanda , Hideo Saito , Vladislav Golyanik

Contrary to conventional frame-based imaging, event-based vision (EBV) or dynamic vision sensing (DVS) asynchronously records binary signals of intensity changes for given pixels with microsecond resolution. The present work explores the…

Fluid Dynamics · Physics 2022-06-22 Christian Willert , Joachim Klinner

Event cameras are becoming increasingly popular in robotics and computer vision due to their beneficial properties, e.g., high temporal resolution, high bandwidth, almost no motion blur, and low power consumption. However, these cameras…

Robotics · Computer Science 2023-03-24 Andreas Ziegler , Daniel Teigland , Jonas Tebbe , Thomas Gossard , Andreas Zell