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Related papers: Temporal Up-Sampling for Asynchronous Events

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This paper presents an algorithm to obtain an event-based video from noisy frames given by physics-based Monte Carlo path tracing over a synthetic 3D scene. Given the nature of dynamic vision sensor (DVS), rendering event-based video can be…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Yuta Tsuji , Tatsuya Yatagawa , Hiroyuki Kubo , Shigeo Morishima

In this work, we propose a novel event based stereo method which addresses the problem of motion blur for a moving event camera. Our method uses the velocity of the camera and a range of disparities to synchronize the positions of the…

Computer Vision and Pattern Recognition · Computer Science 2018-10-22 Alex Zihao Zhu , Yibo Chen , Kostas Daniilidis

We introduce a method for using event camera data in novel view synthesis via Gaussian Splatting. Event cameras offer exceptional temporal resolution and a high dynamic range. Leveraging these capabilities allows us to effectively address…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Toshiya Yura , Ashkan Mirzaei , Igor Gilitschenski

The neuromorphic event cameras, which capture the optical changes of a scene, have drawn increasing attention due to their high speed and low power consumption. However, the event data are noisy, sparse, and nonuniform in the…

Computer Vision and Pattern Recognition · Computer Science 2021-03-23 Chang Liu , Xiaojuan Qi , Edmund Lam , Ngai Wong

Current optical flow and point-tracking methods rely heavily on synthetic datasets. Event cameras are novel vision sensors with advantages in challenging visual conditions, but state-of-the-art frame-based methods cannot be easily adapted…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Friedhelm Hamann , Ziyun Wang , Ioannis Asmanis , Kenneth Chaney , Guillermo Gallego , Kostas Daniilidis

Event cameras respond to brightness changes in the scene asynchronously and independently for every pixel. Due to the properties, these cameras have distinct features: high dynamic range (HDR), high temporal resolution, and low power…

Computer Vision and Pattern Recognition · Computer Science 2022-10-17 Jongwan Kim , DongJin Lee , Byunggook Na , Seongsik Park , Jeonghee Jo , Sungroh Yoon

Event cameras are a kind of bio-inspired sensors that generate data when the brightness changes, which are of low-latency and high dynamic range (HDR). However, due to the nature of the sparse event stream, event-based mapping can only…

Robotics · Computer Science 2021-06-04 Yan Dong

Event cameras asynchronously capture brightness changes with low latency, high temporal resolution, and high dynamic range. However, annotation of event data is a costly and laborious process, which limits the use of deep learning methods…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Simon Klenk , David Bonello , Lukas Koestler , Nikita Araslanov , Daniel Cremers

Event cameras with high dynamic range ensure scene capture even in low-light conditions. However, night events exhibit patterns different from those captured during the day. This difference causes performance degradation when applying night…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Yuhwan Jeong , Hoonhee Cho , Kuk-Jin Yoon

Unlike conventional frame-based sensors, event-based visual sensors output information through spikes at a high temporal resolution. By only encoding changes in pixel intensity, they showcase a low-power consuming, low-latency approach to…

Computer Vision and Pattern Recognition · Computer Science 2019-03-19 Rohan Ghosh , Anupam Gupta , Siyi Tang , Alcimar Soares , Nitish Thakor

Dynamic Vision Sensor (DVS) can asynchronously output the events reflecting apparent motion of objects with microsecond resolution, and shows great application potential in monitoring and other fields. However, the output event stream of…

Computer Vision and Pattern Recognition · Computer Science 2022-03-23 Jinze Chen , Yang Wang , Yang Cao , Feng Wu , Zheng-Jun Zha

How to effectively and efficiently deal with spatio-temporal event streams, where the events are generally sparse and non-uniform and have the microsecond temporal resolution, is of great value and has various real-life applications.…

Computer Vision and Pattern Recognition · Computer Science 2021-07-27 Man Yao , Huanhuan Gao , Guangshe Zhao , Dingheng Wang , Yihan Lin , Zhaoxu Yang , Guoqi Li

Thanks to the rise of wearable and connected devices, sensor-generated time series comprise a large and growing fraction of the world's data. Unfortunately, extracting value from this data can be challenging, since sensors report low-level…

Machine Learning · Statistics 2016-09-30 Davis W. Blalock , John V. Guttag

Adaptive sampling that exploits the spatiotemporal redundancy in videos is critical for always-on action recognition on wearable devices with limited computing and battery resources. The commonly used fixed sampling strategy is not…

Computer Vision and Pattern Recognition · Computer Science 2022-07-18 Khoi-Nguyen C. Mac , Minh N. Do , Minh P. Vo

Event cameras are bio-inspired sensors that capture per-pixel asynchronous intensity change rather than the synchronous absolute intensity frames captured by a classical camera sensor. Such cameras are ideal for robotics applications since…

Computer Vision and Pattern Recognition · Computer Science 2022-05-18 Ziwei Wang , Dingran Yuan , Yonhon Ng , Robert Mahony

Forecasting a typical object's future motion is a critical task for interpreting and interacting with dynamic environments in computer vision. Event-based sensors, which could capture changes in the scene with exceptional temporal…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Song Wu , Zhiyu Zhu , Junhui Hou , Guangming Shi , Jinjian Wu

Lossy compression and rate-adaptive streaming are a mainstay in traditional video steams. However, a new class of neuromorphic ``event'' sensors records video with asynchronous pixel samples rather than image frames. These sensors are…

Image and Video Processing · Electrical Eng. & Systems 2025-08-22 Andrew C. Freeman

Event-based keypoint detection and matching holds significant potential, enabling the integration of event sensors into highly optimized Visual SLAM systems developed for frame cameras over decades of research. Unfortunately, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Yannick Burkhardt , Simon Schaefer , Stefan Leutenegger

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

Perception and decision-making in high-speed dynamic scenarios remain challenging for current robots. In contrast, humans and animals can rapidly perceive and make decisions in such environments. Taking table tennis as a typical example,…

Robotics · Computer Science 2026-04-07 Ziqi Wang , Jingyue Zhao , Xun Xiao , Jichao Yang , Yaohua Wang , Shi Xu , Lei Wang , Huadong Dai
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