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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

Event frame hybrid sensors integrate an Active Pixel Sensor (APS) and an Event Vision Sensor (EVS) within a single chip, combining the high dynamic range and low latency of the EVS with the rich spatial intensity information from the APS.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yunfan Lu , Nico Messikommer , Xiaogang Xu , Liming Chen , Yuhan Chen , Nikola Zubic , Davide Scaramuzza , Hui Xiong

Machine learning models usually assume that a set of feature values used to obtain an output is fixed in advance. However, in many real-world problems, a cost is associated with measuring these features. To address the issue of reducing…

Machine Learning · Computer Science 2025-03-13 Katsumi Takahashi , Koh Takeuchi , Hisashi Kashima

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

Event camera, a novel neuromorphic vision sensor, records data with high temporal resolution and wide dynamic range, offering new possibilities for accurate visual representation in challenging scenarios. However, event data is inherently…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Lin Zhu , Ruonan Liu , Xiao Wang , Lizhi Wang , Hua Huang

Recently, Dynamic Vision Sensors (DVSs) sparked a lot of interest due to their inherent advantages over conventional RGB cameras. These advantages include a low latency, a high dynamic range and a low energy consumption. Nevertheless, the…

Computer Vision and Pattern Recognition · Computer Science 2024-01-05 Katharina Bendig , René Schuster , Didier Stricker

Optical flow is a crucial component of the feature space for early visual processing of dynamic scenes especially in new applications such as self-driving vehicles, drones and autonomous robots. The dynamic vision sensors are well suited…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Himanshu Akolkar , SioHoi Ieng , Ryad Benosman

Aerial surveillance demands rapid and precise detection of moving objects in dynamic environments. Event cameras, which draw inspiration from biological vision systems, present a promising alternative to frame-based sensors due to their…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Sami Arja , Alexandre Marcireau , Saeed Afshar , Bharath Ramesh , Gregory Cohen

Novel view synthesis (NVS) has shown significant promise for applications in cinematographic production, particularly through the exploitation of Neural Radiance Fields (NeRF) and Gaussian Splatting (GS). These methods model real 3D scenes,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Adrian Azzarelli , Nantheera Anantrasirichai , David R Bull

Event-based cameras are dynamic vision sensors that provide asynchronous measurements of changes in per-pixel brightness at a microsecond level. This makes them significantly faster than conventional frame-based cameras, and an appealing…

Computer Vision and Pattern Recognition · Computer Science 2021-10-01 Sai Vemprala , Sami Mian , Ashish Kapoor

Event cameras contain emerging, neuromorphic vision sensors that capture local light intensity changes at each pixel, generating a stream of asynchronous events. This way of acquiring visual information constitutes a departure from…

Computer Vision and Pattern Recognition · Computer Science 2020-10-19 Cian Ryan , Brian O Sullivan , Amr Elrasad , Joe Lemley , Paul Kielty , Christoph Posch , Etienne Perot

Event-based cameras provide accurate and high temporal resolution measurements for performing computer vision tasks in challenging scenarios, such as high-dynamic range environments and fast-motion maneuvers. Despite their advantages,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Mohammad Rostami , Dayuan Jian , Ruitong Sun

This paper proposes an enhancement of convolutional neural networks for object detection in resource-constrained robotics through a geometric input transformation called Visual Mesh. It uses object geometry to create a graph in vision…

Computer Vision and Pattern Recognition · Computer Science 2018-07-24 Trent Houliston , Stephan K. Chalup

Video Scene Graph Generation (VidSGG) aims to capture dynamic relationships among entities by sequentially analyzing video frames and integrating visual and semantic information. However, VidSGG is challenged by significant biases that skew…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Yanjun Li , Zhaoyang Li , Honghui Chen , Lizhi Xu

Event cameras, also known as dynamic vision sensors, are an emerging modality for measuring fast dynamics asynchronously. Event cameras capture changes of log-intensity over time as a stream of 'events' and generally cannot measure…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Ruiming Cao , Dekel Galor , Amit Kohli , Jacob L Yates , Laura Waller

Novel view synthesis (NVS) is a challenging task requiring systems to generate photorealistic images of scenes from new viewpoints, where both quality and speed are important for applications. Previous image-based rendering (IBR) methods…

Computer Vision and Pattern Recognition · Computer Science 2022-08-08 Ang Cao , Chris Rockwell , Justin Johnson

Although 3D Gaussian Splatting (3D-GS) achieves efficient rendering for novel view synthesis, extending it to dynamic scenes still results in substantial memory overhead from replicating Gaussians across frames. To address this challenge,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Chun-Tin Wu , Jun-Cheng Chen

Smart focal-plane and in-chip image processing has emerged as a crucial technology for vision-enabled embedded systems with energy efficiency and privacy. However, the lack of special datasets providing examples of the data that these…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Riadul Islam , Sri Ranga Sai Krishna Tummala , Joey Mulé , Rohith Kankipati , Suraj Jalapally , Dhandeep Challagundla , Chad Howard , Ryan Robucci

Event-based cameras measure intensity changes (called `events') with microsecond accuracy under high-speed motion and challenging lighting conditions. With the `active pixel sensor' (APS), the `Dynamic and Active-pixel Vision Sensor'…

Computer Vision and Pattern Recognition · Computer Science 2020-11-13 Liyuan Pan , Richard Hartley , Cedric Scheerlinck , Miaomiao Liu , Xin Yu , Yuchao Dai

Bio-inspired event cameras have recently attracted significant research due to their asynchronous and low-latency capabilities. These features provide a high dynamic range and significantly reduce motion blur. However, because of the…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Aheli Saha , René Schuster , Didier Stricker