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We present an approach for object segmentation in videos that combines frame-level object detection with concepts from object tracking and motion segmentation. The approach extracts temporally consistent object tubes based on an…

Computer Vision and Pattern Recognition · Computer Science 2016-08-11 Benjamin Drayer , Thomas Brox

Event cameras, often referred to as dynamic vision sensors, are groundbreaking sensors capable of capturing changes in light intensity asynchronously, offering exceptional temporal resolution and energy efficiency. These attributes make…

Computer Vision and Pattern Recognition · Computer Science 2025-02-27 Mira Adra , Simone Melcarne , Nelida Mirabet-Herranz , Jean-Luc Dugelay

Event cameras are rapidly emerging as powerful vision sensors for 3D reconstruction, uniquely capable of asynchronously capturing per-pixel brightness changes. Compared to traditional frame-based cameras, event cameras produce sparse yet…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Chuanzhi Xu , Haoxian Zhou , Langyi Chen , Haodong Chen , Zeke Zexi Hu , Zhicheng Lu , Ying Zhou , Vera Chung , Qiang Qu , Weidong Cai

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…

Robotics · Computer Science 2022-02-09 Kun Xiao , Guohui Wang , Yi Chen , Yongfeng Xie , Hong Li , Sen Li

Vision-based localization is a cost-effective and thus attractive solution for many intelligent mobile platforms. However, its accuracy and especially robustness still suffer from low illumination conditions, illumination changes, and…

Robotics · Computer Science 2024-01-17 Yi-Fan Zuo , Wanting Xu , Xia Wang , Yifu Wang , Laurent Kneip

3D object detection is essential for autonomous systems, enabling precise localization and dimension estimation. While LiDAR and RGB cameras are widely used, their fixed frame rates create perception gaps in high-speed scenarios. Event…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Jae-Young Kang , Hoonhee Cho , Kuk-Jin Yoon

In this work, we present optical space imaging using an unconventional yet promising class of imaging devices known as neuromorphic event-based sensors. These devices, which are modeled on the human retina, do not operate with frames, but…

Computer Vision and Pattern Recognition · Computer Science 2019-11-21 Saeed Afshar , Andrew P Nicholson , Andre van Schaik , Gregory Cohen

Visual segmentation is a key perceptual function that partitions visual space and allows for detection, recognition and discrimination of objects in complex environments. The processes underlying human segmentation of natural images are…

Computer Vision and Pattern Recognition · Computer Science 2019-05-03 Jonathan Vacher , Pascal Mamassian , Ruben Coen-Cagli

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, inspired by biological vision systems, provide a natural and data efficient representation of visual information. Visual information is acquired in the form of events that are triggered by local brightness changes. Each pixel…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Cheng Gu , Erik Learned-Miller , Daniel Sheldon , Guillermo Gallego , Pia Bideau

Event cameras are bio-inspired visual sensors that capture pixel-wise intensity changes and output asynchronous event streams. They show great potential over conventional cameras to handle challenging scenarios in robotics and computer…

Robotics · Computer Science 2024-06-07 Shuang Guo , Guillermo Gallego

Event cameras provide asynchronous, data-driven measurements of local temporal contrast over a large dynamic range with extremely high temporal resolution. Conventional cameras capture low-frequency reference intensity information. These…

Computer Vision and Pattern Recognition · Computer Science 2018-11-02 Cedric Scheerlinck , Nick Barnes , Robert Mahony

This paper presents a method for automatic video object segmentation based on the fusion of motion stream, appearance stream, and instance-aware segmentation. The proposed scheme consists of a two-stream fusion network and an instance…

Computer Vision and Pattern Recognition · Computer Science 2019-12-04 Sungkwon Choo , Wonkyo Seo , Nam Ik Cho

Non-uniform image deblurring is a challenging task due to the lack of temporal and textural information in the blurry image itself. Complementary information from auxiliary sensors such event sensors are being explored to address these…

Computer Vision and Pattern Recognition · Computer Science 2022-08-25 Patricia Vitoria , Stamatios Georgoulis , Stepan Tulyakov , Alfredo Bochicchio , Julius Erbach , Yuanyou Li

Event cameras are bio-inspired sensors that asynchronously report intensity changes in microsecond resolution. DAVIS can capture high dynamics of a scene and simultaneously output high temporal resolution events and low frame-rate intensity…

Computer Vision and Pattern Recognition · Computer Science 2020-04-02 Liyuan Pan , Miaomiao Liu , Richard Hartley

Event cameras are neuromorphically inspired sensors that sparsely and asynchronously report brightness changes. Their unique characteristics of high temporal resolution, high dynamic range, and low power consumption make them well-suited…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Haitao Meng , Chonghao Zhong , Sheng Tang , Lian JunJia , Wenwei Lin , Zhenshan Bing , Yi Chang , Gang Chen , Alois Knoll

Event cameras or neuromorphic cameras mimic the human perception system as they measure the per-pixel intensity change rather than the actual intensity level. In contrast to traditional cameras, such cameras capture new information about…

Computer Vision and Pattern Recognition · Computer Science 2016-08-05 Christian Reinbacher , Gottfried Graber , Thomas Pock

We present the first purely event-based, energy-efficient approach for object detection and categorization using an event camera. Compared to traditional frame-based cameras, choosing event cameras results in high temporal resolution (order…

Computer Vision and Pattern Recognition · Computer Science 2019-04-30 Bharath Ramesh , Andres Ussa , Luca Della Vedova , Hong Yang , Garrick Orchard

Event cameras excel in capturing high-contrast scenes and dynamic objects, offering a significant advantage over traditional frame-based cameras. Despite active research into leveraging event cameras for semantic segmentation, generating…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Hoonhee Cho , Sung-Hoon Yoon , Hyeokjun Kweon , Kuk-Jin Yoon

Capturing a 3D human body is one of the important tasks in computer vision with a wide range of applications such as virtual reality and sports analysis. However, conventional frame cameras are limited by their temporal resolution and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Kai Kohyama , Shintaro Shiba , Yoshimitsu Aoki
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