English
Related papers

Related papers: FEDORA: Flying Event Dataset fOr Reactive behAvior

200 papers

Recent learning-based methods for event-based optical flow estimation utilize cost volumes for pixel matching but suffer from redundant computations and limited scalability to higher resolutions for flow refinement. In this work, we take…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Daikun Liu , Lei Cheng , Teng Wang , changyin Sun

Event-based cameras have recently drawn the attention of the Computer Vision community thanks to their advantages in terms of high temporal resolution, low power consumption and high dynamic range, compared to traditional frame-based…

Computer Vision and Pattern Recognition · Computer Science 2018-03-22 Amos Sironi , Manuele Brambilla , Nicolas Bourdis , Xavier Lagorce , Ryad Benosman

Tracking using bio-inspired event cameras has drawn more and more attention in recent years. Existing works either utilize aligned RGB and event data for accurate tracking or directly learn an event-based tracker. The first category needs…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Xiao Wang , Shiao Wang , Chuanming Tang , Lin Zhu , Bo Jiang , Yonghong Tian , Jin Tang

With the success of deep learning, object recognition systems that can be deployed for real-world applications are becoming commonplace. However, inference that needs to largely take place on the `edge' (not processed on servers), is a…

Computer Vision and Pattern Recognition · Computer Science 2020-01-30 Andres Ussa , Luca Della Vedova , Vandana Reddy Padala , Deepak Singla , Jyotibdha Acharya , Charles Zhang Lei , Garrick Orchard , Arindam Basu , Bharath Ramesh

Fast-flying aerial robots promise rapid inspection under limited battery constraints, with direct applications in infrastructure inspection, terrain exploration, and search and rescue. However, high speeds lead to severe motion blur in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Rong Zou , Marco Cannici , Davide Scaramuzza

Event cameras are motion-activated sensors that capture pixel-level illumination changes instead of the intensity image with a fixed frame rate. Compared with the standard cameras, it can provide reliable visual perception during high-speed…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Weipeng Guan , Peiyu Chen , Yuhan Xie , Peng Lu

This work introduces a novel and adaptable architecture designed for real-time occupancy forecasting that outperforms existing state-of-the-art models on the Waymo Open Motion Dataset in Soft IOU. The proposed model uses recursive latent…

Robotics · Computer Science 2024-02-05 Bryce Ferenczi , Michael Burke , Tom Drummond

Event cameras are novel sensors that report 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 temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2019-06-19 Henri Rebecq , René Ranftl , Vladlen Koltun , Davide Scaramuzza

Efficient processing of high-res video streams is safety-critical for many robotics applications such as autonomous driving. To maintain real-time performance, many practical systems downsample the video stream. But this can hurt downstream…

Computer Vision and Pattern Recognition · Computer Science 2021-10-12 Chittesh Thavamani , Mengtian Li , Nicolas Cebron , Deva Ramanan

Event-based cameras capture visual information as asynchronous streams of per-pixel brightness changes, generating sparse, temporally precise data. Compared to conventional frame-based sensors, they offer significant advantages in capturing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Biswadeep Sen , Benoit R. Cottereau , Nicolas Cuperlier , Terence Sim

Camera traps offer enormous new opportunities in ecological studies, but current automated image analysis methods often lack the contextual richness needed to support impactful conservation outcomes. Here we present an integrated approach…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Paul Fergus , Carl Chalmers , Naomi Matthews , Stuart Nixon , Andre Burger , Oliver Hartley , Chris Sutherland , Xavier Lambin , Steven Longmore , Serge Wich

We present Recurrent Vision Transformers (RVTs), a novel backbone for object detection with event cameras. Event cameras provide visual information with sub-millisecond latency at a high-dynamic range and with strong robustness against…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Mathias Gehrig , Davide Scaramuzza

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

In this work, we present optical space imaging using an unconventional yet promising class of imaging devices known as neuromorphic event-based sensors. These devices, which are modeled on the human retina, do not operate with frames, but…

Computer Vision and Pattern Recognition · Computer Science 2019-11-21 Saeed Afshar , Andrew P Nicholson , Andre van Schaik , Gregory Cohen

Event cameras provide microsecond-level temporal resolution, low latency, and high dynamic range, offering potential for perception under fast motion and challenging illumination conditions. However, existing Event-based Object Detection…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Meisen Wang , Hao Deng , Wei Bao , Ma Yuanxiao , Chengjie Wang , Zhiqiang Tian , Shaoyi Du , Siqi Li

Generating videos guided by camera trajectories poses significant challenges in achieving consistency and generalizability, particularly when both camera and object motions are present. Existing approaches often attempt to learn these…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Guojun Lei , Chi Wang , Yikai Wang , Hong Li , Ying Song , Weiwei Xu

Event cameras are a novel type of biologically inspired vision sensor known for their high temporal resolution, high dynamic range, and low power consumption. Because of these properties, they are well-suited for processing fast motions…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Ziyun Wang , Jinyuan Guo , Kostas Daniilidis

The swift advancement of unmanned aerial vehicle (UAV) technologies necessitates new standards for developing human-drone interaction (HDI) interfaces. Most interfaces for HDI, especially first-person view (FPV) goggles, limit the…

In recent years there has been a growing interest in event cameras, i.e. vision sensors that record changes in illumination independently for each pixel. This type of operation ensures that acquisition is possible in very adverse lighting…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Tomasz Kryjak

Event-based approaches, which are based on bio-inspired asynchronous event cameras, have achieved promising performance on various computer vision tasks. However, the study of the fundamental event data association problem is still in its…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Haosheng Chen , Yue Wu , Yidong Peng