Event-based vision: A survey
Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead
of capturing images at a fixed rate, they asynchronously measure per-pixel brightness …
of capturing images at a fixed rate, they asynchronously measure per-pixel brightness …
[HTML][HTML] Deep learning with spiking neurons: opportunities and challenges
M Pfeiffer, T Pfeil - Frontiers in neuroscience, 2018 - frontiersin.org
Spiking neural networks (SNNs) are inspired by information processing in biology, where
sparse and asynchronous binary signals are communicated and processed in a massively …
sparse and asynchronous binary signals are communicated and processed in a massively …
Aegnn: Asynchronous event-based graph neural networks
S Schaefer, D Gehrig… - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
The best performing learning algorithms devised for event cameras work by first converting
events into dense representations that are then processed using standard CNNs. However …
events into dense representations that are then processed using standard CNNs. However …
High speed and high dynamic range video with an event camera
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 …
asynchronous “events” instead of intensity frames. They offer significant advantages with …
Learning to detect objects with a 1 megapixel event camera
E Perot, P De Tournemire, D Nitti… - Advances in Neural …, 2020 - proceedings.neurips.cc
Event cameras encode visual information with high temporal precision, low data-rate, and
high-dynamic range. Thanks to these characteristics, event cameras are particularly suited …
high-dynamic range. Thanks to these characteristics, event cameras are particularly suited …
Unsupervised event-based learning of optical flow, depth, and egomotion
In this work, we propose a novel framework for unsupervised learning for event cameras that
learns motion information from only the event stream. In particular, we propose an input …
learns motion information from only the event stream. In particular, we propose an input …
Event-based fusion for motion deblurring with cross-modal attention
Traditional frame-based cameras inevitably suffer from motion blur due to long exposure
times. As a kind of bio-inspired camera, the event camera records the intensity changes in …
times. As a kind of bio-inspired camera, the event camera records the intensity changes in …
Events-to-video: Bringing modern computer vision to event cameras
Event cameras are novel sensors that report brightness changes in the form of
asynchronous" events" instead of intensity frames. They have significant advantages over …
asynchronous" events" instead of intensity frames. They have significant advantages over …
Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age
Simultaneous localization and mapping (SLAM) consists in the concurrent construction of a
model of the environment (the map), and the estimation of the state of the robot moving …
model of the environment (the map), and the estimation of the state of the robot moving …
Object detection with spiking neural networks on automotive event data
L Cordone, B Miramond… - 2022 International Joint …, 2022 - ieeexplore.ieee.org
Automotive embedded algorithms have very high constraints in terms of latency, accuracy
and power consumption. In this work, we propose to train spiking neural networks (SNNs) …
and power consumption. In this work, we propose to train spiking neural networks (SNNs) …