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Visual reconstruction of fast non-rigid object deformations over time is a challenge for conventional frame-based cameras. In this paper, we propose a novel approach for reconstructing such deformations using measurements from event-based…

Computer Vision and Pattern Recognition · Computer Science 2022-11-15 Yuxuan Xue , Haolong Li , Stefan Leutenegger , Jörg Stückler

Event-based cameras, inspired by the biological retina, have evolved into cutting-edge sensors distinguished by their minimal power requirements, negligible latency, superior temporal resolution, and expansive dynamic range. At present,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Han Wang , Yuman Nie , Yun Li , Hongjie Liu , Min Liu , Wen Cheng , Yaoxiong Wang

Event cameras provide microsecond latency, making them suitable for 6D object pose tracking in fast, dynamic scenes where conventional RGB and depth pipelines suffer from motion blur and large pixel displacements. We introduce EventTrack6D,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Jae-Young Kang , Hoonhee Cho , Taeyeop Lee , Minjun Kang , Bowen Wen , Youngho Kim , 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

We propose a novel ConvNet model for predicting 2D human body poses in an image. The model regresses a heatmap representation for each body keypoint, and is able to learn and represent both the part appearances and the context of the part…

Computer Vision and Pattern Recognition · Computer Science 2017-08-08 Vasileios Belagiannis , Andrew Zisserman

Event cameras are bio-inspired, motion-activated sensors that demonstrate substantial potential in handling challenging situations, such as motion blur and high-dynamic range. In this paper, we proposed EVI-SAM to tackle the problem of 6…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Weipeng Guan , Peiyu Chen , Huibin Zhao , Yu Wang , Peng Lu

Event cameras offer multiple advantages in monocular egocentric 3D human pose estimation from head-mounted devices, such as millisecond temporal resolution, high dynamic range, and negligible motion blur. Existing methods effectively…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Mayur Deshmukh , Hiroyasu Akada , Helge Rhodin , Christian Theobalt , Vladislav Golyanik

The event camera is a novel bio-inspired vision sensor. When the brightness change exceeds the preset threshold, the sensor generates events asynchronously. The number of valid events directly affects the performance of event-based tasks,…

Computer Vision and Pattern Recognition · Computer Science 2022-08-24 Xijie Xiang , Lin Zhu , Jianing Li , Yonghong Tian , Tiejun Huang

Event cameras are a bio-inspired class of sensors that asynchronously measure per-pixel intensity changes. Under fixed illumination conditions in static or low-motion scenes, rigidly mounted event cameras are unable to generate any events…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Vincenzo Polizzi , Stephen Yang , Quentin Clark , Jonathan Kelly , Igor Gilitschenski , David B. Lindell

The broad scope of obstacle avoidance has led to many kinds of computer vision-based approaches. Despite its popularity, it is not a solved problem. Traditional computer vision techniques using cameras and depth sensors often focus on…

Computer Vision and Pattern Recognition · Computer Science 2022-12-06 Celyn Walters , Simon Hadfield

Event cameras are dynamic vision sensors inspired by the biological retina, characterized by their high dynamic range, high temporal resolution, and low power consumption. These features make them capable of perceiving 3D environments even…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Hoonhee Cho , Jae-Young Kang , Kuk-Jin Yoon

An event camera detects per-pixel intensity difference and produces asynchronous event stream with low latency, high dynamic range, and low power consumption. As a trade-off, the event camera has low spatial resolution. We propose an…

Computer Vision and Pattern Recognition · Computer Science 2020-04-13 S. Mohammad Mostafavi I. , Jonghyun Choi , Kuk-Jin Yoon

We present a method that leverages the complementarity of event cameras and standard cameras to track visual features with low-latency. Event cameras are novel sensors that output pixel-level brightness changes, called "events". They offer…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Daniel Gehrig , Henri Rebecq , Guillermo Gallego , Davide Scaramuzza

We focus on a very challenging task: imaging at nighttime dynamic scenes. Most previous methods rely on the low-light enhancement of a conventional RGB camera. However, they would inevitably face a dilemma between the long exposure time of…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Haoyue Liu , Shihan Peng , Lin Zhu , Yi Chang , Hanyu Zhou , Luxin Yan

Event-based vision sensors mimic the operation of biological retina and they represent a major paradigm shift from traditional cameras. Instead of providing frames of intensity measurements synchronously, at artificially chosen rates,…

Computer Vision and Pattern Recognition · Computer Science 2015-10-08 Guillermo Gallego , Christian Forster , Elias Mueggler , Davide Scaramuzza

Event cameras are novel sensors that output brightness changes in the form of a stream of asynchronous events instead of intensity frames. Compared to conventional image sensors, they offer significant advantages: high temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2020-10-23 Javier Hidalgo-Carrió , Daniel Gehrig , Davide Scaramuzza

Previous video-based human pose estimation methods have shown promising results by leveraging aggregated features of consecutive frames. However, most approaches compromise accuracy to mitigate jitter or do not sufficiently comprehend the…

Computer Vision and Pattern Recognition · Computer Science 2022-11-30 Kyung-Min Jin , Byoung-Sung Lim , Gun-Hee Lee , Tae-Kyung Kang , Seong-Whan Lee

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

Event cameras are novel sensors that output brightness changes in the form of a stream of asynchronous "events" instead of intensity frames. They offer significant advantages with respect to conventional cameras: high dynamic range (HDR),…

Computer Vision and Pattern Recognition · Computer Science 2020-04-02 Daniel Gehrig , Mathias Gehrig , Javier Hidalgo-Carrió , Davide Scaramuzza

Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. They offer significant advantages over standard cameras, namely a very high dynamic range, no motion blur, and a…

Robotics · Computer Science 2019-01-21 Elias Mueggler , Guillermo Gallego , Henri Rebecq , Davide Scaramuzza