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Event cameras, mimicking the human retina, capture brightness changes with unparalleled temporal resolution and dynamic range. Integrating events into intensities poses a highly ill-posed challenge, marred by initial condition ambiguities.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Jinxiu Liang , Bohan Yu , Yixin Yang , Yiming Han , Boxin Shi

Event cameras are a new type of sensors that are different from traditional cameras. Each pixel is triggered asynchronously by event. The trigger event is the change of the brightness irradiated on the pixel. If the increment or decrement…

Computer Vision and Pattern Recognition · Computer Science 2022-03-24 Kun Xiao , Guohui Wang , Yi Chen , Jinghong Nan , Yongfeng Xie

Event-based cameras (EBCs) have emerged as a bio-inspired alternative to traditional cameras, offering advantages in power efficiency, temporal resolution, and high dynamic range. However, the development of image analysis methods for EBCs…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Dmitrii Torbunov , Yihui Ren , Animesh Ghose , Odera Dim , Yonggang Cui

As an alternative sensing paradigm, dynamic vision sensors (DVS) have been recently explored to tackle scenarios where conventional sensors result in high data rate and processing time. This paper presents a hybrid event-frame approach for…

Computer Vision and Pattern Recognition · Computer Science 2022-05-11 Vivek Mohan , Deepak Singla , Tarun Pulluri , Andres Ussa , Pradeep Kumar Gopalakrishnan , Pao-Sheng Sun , Bharath Ramesh , Arindam Basu

Event-based cameras are bio-inspired sensors that detect light changes asynchronously for each pixel. They are increasingly used in fields like computer vision and robotics because of several advantages over traditional frame-based cameras,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 Andreas Ziegler , David Joseph , Thomas Gossard , Emil Moldovan , Andreas Zell

Unwanted camera occlusions, such as debris, dust, rain-drops, and snow, can severely degrade the performance of computer-vision systems. Dynamic occlusions are particularly challenging because of the continuously changing pattern. Existing…

Computer Vision and Pattern Recognition · Computer Science 2023-08-02 Rong Zou , Manasi Muglikar , Nico Messikommer , Davide Scaramuzza

Event cameras offering high dynamic range and low latency have emerged as disruptive technologies in imaging. Despite growing research on leveraging these benefits for different imaging tasks, a comprehensive study of recently advances and…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Yunfan Lu , Xiaogang Xu , Pengteng Li , Yusheng Wang , Yi Cui , Huizai Yao , Hui Xiong

Event cameras are novel vision sensors that report per-pixel brightness changes as a stream of asynchronous "events". They offer significant advantages compared to standard cameras due to their high temporal resolution, high dynamic range…

Computer Vision and Pattern Recognition · Computer Science 2021-02-19 Daniel Gehrig , Michelle Rüegg , Mathias Gehrig , Javier Hidalgo Carrio , Davide Scaramuzza

Event cameras are novel vision sensors that sample, in an asynchronous fashion, brightness increments with low latency and high temporal resolution. The resulting streams of events are of high value by themselves, especially for high speed…

Computer Vision and Pattern Recognition · Computer Science 2021-04-13 F. Paredes-Vallés , G. C. H. E. de Croon

Event cameras are bio-inspired sensors that offer advantages over traditional cameras. They operate asynchronously, sampling the scene at microsecond resolution and producing a stream of brightness changes. This unconventional output has…

Computer Vision and Pattern Recognition · Computer Science 2022-09-14 Suman Ghosh , Guillermo Gallego

Accurate perception of dynamic obstacles is essential for autonomous robot navigation in indoor environments. Although sophisticated 3D object detection and tracking methods have been investigated and developed thoroughly in the fields of…

Robotics · Computer Science 2025-03-03 Zhefan Xu , Haoyu Shen , Xinming Han , Hanyu Jin , Kanlong Ye , Kenji Shimada

Event cameras rely on motion to obtain information about scene appearance. This means that appearance and motion are inherently linked: either both are present and recorded in the event data, or neither is captured. Previous works treat the…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Shuang Guo , Friedhelm Hamann , Guillermo Gallego

Event cameras and LiDARs provide complementary yet distinct data: respectively, asynchronous detections of changes in lighting versus sparse but accurate depth information at a fixed rate. To this day, few works have explored the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Vincent Brebion , Julien Moreau , Franck Davoine

Event cameras, offering high temporal resolutions and high dynamic ranges, have brought a new perspective to address common challenges (e.g., motion blur and low light) in monocular depth estimation. However, how to effectively exploit the…

Computer Vision and Pattern Recognition · Computer Science 2022-12-07 Xu Liu , Jianing Li , Xiaopeng Fan , Yonghong Tian

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 cameras are bio-inspired sensors that perform well in challenging illumination conditions and have high temporal resolution. However, their concept is fundamentally different from traditional frame-based cameras. The pixels of an…

Computer Vision and Pattern Recognition · Computer Science 2022-06-13 Xin Peng , Ling Gao , Yifu Wang , Laurent Kneip

Rapid and reliable identification of dynamic scene parts, also known as motion segmentation, is a key challenge for mobile sensors. Contemporary RGB camera-based methods rely on modeling camera and scene properties however, are often…

Computer Vision and Pattern Recognition · Computer Science 2024-03-08 Stamatios Georgoulis , Weining Ren , Alfredo Bochicchio , Daniel Eckert , Yuanyou Li , Abel Gawel

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

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

3D shape reconstruction is a primary component of augmented/virtual reality. Despite being highly advanced, existing solutions based on RGB, RGB-D and Lidar sensors are power and data intensive, which introduces challenges for deployment in…

Computer Vision and Pattern Recognition · Computer Science 2020-12-11 Alexis Baudron , Zihao W. Wang , Oliver Cossairt , Aggelos K. Katsaggelos