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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

In the field of video analytics, particularly traffic surveillance, there is a growing need for efficient and effective methods for processing and understanding video data. Traditional full video decoding techniques can be computationally…

Computer Vision and Pattern Recognition · Computer Science 2023-08-08 Muhammet Sebul Beratoğlu , Behçet Uğur Töreyin

Scene reconstruction from casually captured videos has wide applications in real-world scenarios. With recent advancements in differentiable rendering techniques, several methods have attempted to simultaneously optimize scene…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Bohao Liao , Wei Zhai , Zengyu Wan , Zhixin Cheng , Wenfei Yang , Tianzhu Zhang , Yang Cao , Zheng-Jun Zha

Event cameras are bio-inspired sensors providing significant advantages over standard cameras such as low latency, high temporal resolution, and high dynamic range. We propose a novel structured-light system using an event camera to tackle…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Manasi Muglikar , Guillermo Gallego , Davide Scaramuzza

Event-based cameras are vision devices that transmit only brightness changes with low latency and ultra-low power consumption. Such characteristics make event-based cameras attractive in the field of localization and object tracking in…

Computer Vision and Pattern Recognition · Computer Science 2020-10-30 Sherif A. S. Mohamed , Jawad N. Yasin , Mohammad-hashem Haghbayan , Antonio Miele , Jukka Heikkonen , Hannu Tenhunen , Juha Plosila

The advantages of event-sensing over conventional sensors (e.g., higher dynamic range, lower time latency, and lower power consumption) have spurred research into machine learning for event data. Unsurprisingly, deep learning has emerged as…

Machine Learning · Computer Science 2021-06-11 Fuqiang Gu , Weicong Sng , Xuke Hu , Fangwen Yu

This work introduces a robot navigation controller that combines event cameras and other sensors with reinforcement learning to enable real-time human-centered navigation and obstacle avoidance. Unlike conventional image-based controllers,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Ignacio Bugueno-Cordova , Javier Ruiz-del-Solar , Rodrigo Verschae

Compared to conventional cameras, event cameras provide a high dynamic range and low latency, offering greater robustness to rapid motion and challenging lighting conditions. Although the potential of event cameras for visual place…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Therese Joseph , Tobias Fischer , Michael Milford

Neuromorphic vision sensors or event cameras have made the visual perception of extremely low reaction time possible, opening new avenues for high-dynamic robotics applications. These event cameras' output is dependent on both motion and…

Recent advancements in neural network-based optical flow estimation often come with prohibitively high computational and memory requirements, presenting challenges in their model adaptation for mobile and low-power use cases. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2023-06-12 Risheek Garrepalli , Jisoo Jeong , Rajeswaran C Ravindran , Jamie Menjay Lin , Fatih Porikli

Event cameras are bio-inspired vision sensor that encode visual information with high dynamic range, high temporal resolution, and low latency.Current state-of-the-art event stream processing methods rely on end-to-end deep learning…

Neurons and Cognition · Quantitative Biology 2025-10-01 Yu Chen , Jing Lian , Zhaofei Yu , Jizhao Liu , Jisheng Dang , Gang Wang

With their motion-responsive nature, event-based cameras offer significant advantages over traditional cameras for optical flow estimation. While deep learning has improved upon traditional methods, current neural networks adopted for…

Computer Vision and Pattern Recognition · Computer Science 2025-04-16 Gokul Raju Govinda Raju , Nikola Zubić , Marco Cannici , Davide Scaramuzza

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

Tracking any point based on image frames is constrained by frame rates, leading to instability in high-speed scenarios and limited generalization in real-world applications. To overcome these limitations, we propose an image-event fusion…

Computer Vision and Pattern Recognition · Computer Science 2024-09-19 Jiaxiong Liu , Bo Wang , Zhen Tan , Jinpu Zhang , Hui Shen , Dewen Hu

Event cameras offer promising advantages such as high dynamic range and low latency, making them well-suited for challenging lighting conditions and fast-moving scenarios. However, reconstructing 3D scenes from raw event streams is…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Jiaxu Wang , Junhao He , Ziyi Zhang , Mingyuan Sun , Jingkai Sun , Renjing Xu

Explicit feature-grid based NeRF models have shown promising results in terms of rendering quality and significant speed-up in training. However, these methods often require a significant amount of data to represent a single scene or…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Soonbin Lee , Fangwen Shu , Yago Sanchez , Thomas Schierl , Cornelius Hellge

Cross-platform adaptation in event-based dense perception is crucial for deploying event cameras across diverse settings, such as vehicles, drones, and quadrupeds, each with unique motion dynamics, viewpoints, and class distributions. In…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Lingdong Kong , Dongyue Lu , Xiang Xu , Lai Xing Ng , Wei Tsang Ooi , Benoit R. Cottereau

Volumetric videos, benefiting from immersive 3D realism and interactivity, hold vast potential for various applications, while the tremendous data volume poses significant challenges for compression. Recently, NeRF has demonstrated…

Computer Vision and Pattern Recognition · Computer Science 2024-11-11 Zhiyu Zhang , Guo Lu , Huanxiong Liang , Anni Tang , Qiang Hu , Li Song

Event cameras are bio-inspired vision sensors that asynchronously measure per-pixel brightness changes.The high-temporal resolution and asynchronicity of event cameras offer great potential for estimating robot motion states. Recent works…

Robotics · Computer Science 2025-01-07 Zhixiang Wang , Xudong Li , Yizhai Zhang , Panfeng Huang

Pixelated detectors in scanning transmission electron microscopy (STEM) generate large volumes of data, often tens to hundreds of GB per scan. However, to make current advancements scalable and enable widespread adoption, it is essential to…

Instrumentation and Detectors · Physics 2025-07-16 Arno Annys , Hoelen L. Lalandec Robert , Saleh Gholam , Joke Hadermann , Jo Verbeeck
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