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Although low-rank and sparse decomposition based methods have been successfully applied to the problem of moving object detection using structured sparsity-inducing norms, they are still vulnerable to significant illumination changes that…

Computer Vision and Pattern Recognition · Computer Science 2019-04-09 Moein Shakeri , Hong Zhang

This paper proposes the use of an event camera as a component of a vision system that enables counting of fast-moving objects - in this case, falling corn grains. These type of cameras transmit information about the change in brightness of…

Computer Vision and Pattern Recognition · Computer Science 2023-11-14 Kamil Bialik , Marcin Kowalczyk , Krzysztof Blachut , Tomasz Kryjak

Most commercially available Light Detection and Ranging (LiDAR)s measure the distances along a 2D section of the environment by sequentially sampling the free range along directions centered at the sensor's origin. When the sensor moves…

Robotics · Computer Science 2023-10-17 Omar Salem , Emanuele Giacomini , Leonardo Brizi , Luca Di Giammarino , Giorgio Grisetti

Event-based bionic camera asynchronously captures dynamic scenes with high temporal resolution and high dynamic range, offering potential for the integration of events and RGB under conditions of illumination degradation and fast motion.…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Pengcheng Shao , Tianyang Xu , Xuefeng Zhu , Xiaojun Wu , Josef Kittler

We propose to incorporate feature correlation and sequential processing into dense optical flow estimation from event cameras. Modern frame-based optical flow methods heavily rely on matching costs computed from feature correlation. In…

Computer Vision and Pattern Recognition · Computer Science 2021-10-22 Mathias Gehrig , Mario Millhäusler , Daniel Gehrig , Davide Scaramuzza

Event-based cameras (ECs) have emerged as bio-inspired sensors that report pixel brightness changes asynchronously, offering unmatched speed and efficiency in vision sensing. Despite their high dynamic range, temporal resolution, low power…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Seyed Ehsan Marjani Bajestani , Giovanni Beltrame

Event cameras are renowned for their high efficiency due to outputting a sparse, asynchronous stream of events. However, they are plagued by noisy events, especially in low light conditions. Denoising is an essential task for event cameras,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Chenyang Shi , Shasha Guo , Boyi Wei , Hanxiao Liu , Yibo Zhang , Ningfang Song , Jing Jin

Due to the extremely low latency, events have been recently exploited to supplement lost information for motion deblurring. Existing approaches largely rely on the perfect pixel-wise alignment between intensity images and events, which is…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Mingyuan Lin , Chi Zhang , Chu He , Lei Yu

The fields of imaging in the nighttime dynamic and other extremely dark conditions have seen impressive and transformative advancements in recent years, partly driven by the rise of novel sensing approaches, e.g., near-infrared (NIR)…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Chao Qu , Shuo Zhu , Yuhang Wang , Zongze Wu , Xiaoyu Chen , Edmund Y. Lam , Jing Han

Event cameras are vision sensors that record asynchronous streams of per-pixel brightness changes, referred to as "events". They have appealing advantages over frame-based cameras for computer vision, including high temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-21 Daniel Gehrig , Antonio Loquercio , Konstantinos G. Derpanis , Davide Scaramuzza

We apply a Machine Learning technique known as Convolutional Denoising Autoencoder to denoise synthetic images of state-of-the-art radio telescopes, with the goal of detecting the faint, diffused radio sources predicted to characterise the…

Instrumentation and Methods for Astrophysics · Physics 2021-11-03 Claudio Gheller , Franco Vazza

Understanding lattice deformations is crucial in determining the properties of nanomaterials, which can become more prominent in future applications ranging from energy harvesting to electronic devices. However, it remains challenging to…

Reconstructing Dynamic 3D Gaussian Splatting (3DGS) from low-framerate RGB videos is challenging. This is because large inter-frame motions will increase the uncertainty of the solution space. For example, one pixel in the first frame might…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Junhao He , Jiaxu Wang , Jia Li , Mingyuan Sun , Qiang Zhang , Jiahang Cao , Ziyi Zhang , Yi Gu , Jingkai Sun , Renjing Xu

During construction, continuous monitoring of underground tunnels can mitigate potential hazards and facilitate an in-depth understanding of the ground-tunnel interaction behavior. Traditional vision-based monitoring can directly capture an…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Kecheng Chen , Hiroshi Kogi , Kenichi Soga

Sound Event Detection (SED) aims to predict the temporal boundaries of all the events of interest and their class labels, given an unconstrained audio sample. Taking either the splitand-classify (i.e., frame-level) strategy or the more…

Sound · Computer Science 2023-08-21 Swapnil Bhosale , Sauradip Nag , Diptesh Kanojia , Jiankang Deng , Xiatian Zhu

This paper proposes a novel two-stream encoder-decoder network, which utilizes both the high-level and the low-level image features for precisely localizing forged regions in a manipulated image. This is motivated from the fact that the…

Computer Vision and Pattern Recognition · Computer Science 2020-09-29 Aniruddha Mazumdar , Prabin Kumar Bora

Ultrafast-optical-pump -- structural-probe measurements, including ultrafast electron and x-ray scattering, provide direct experimental access to the fundamental timescales of atomic motion, and are thus foundational techniques for studying…

Compared to regular cameras, Dynamic Vision Sensors or Event Cameras can output compact visual data based on a change in the intensity in each pixel location asynchronously. In this paper, we study the application of current image-based…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Masoud Dayani Najafabadi , Mohammad Reza Ahmadzadeh

Neuromorphic imaging reacts to per-pixel brightness changes of a dynamic scene with high temporal precision and responds with asynchronous streaming events as a result. It also often supports a simultaneous output of an intensity image.…

Image and Video Processing · Electrical Eng. & Systems 2024-03-25 Pei Zhang , Haosen Liu , Zhou Ge , Chutian Wang , Edmund Y. Lam

In this paper we compare event-based decaying and time based-decaying memory surfaces for high-speed eventbased tracking, feature extraction, and object classification using an event-based camera. The high-speed recognition task involves…

Neural and Evolutionary Computing · Computer Science 2017-11-09 Saeed Afshar , Gregory Cohen , Tara Julia Hamilton , Jonathan Tapson , Andre van Schaik
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