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20182022
most citedA Large Scale Event-based Detection Dataset for Automotive

67 citations · 73 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.CV20226 cited

Long-Lived Accurate Keypoints in Event Streams

Philippe Chiberre, Etienne Perot, Amos Sironi +1

We present a novel end-to-end approach to keypoint detection and tracking in an event stream that provides better precision and much longer keypoint tracks than previous methods. T…

cs.CV2020

Real-Time Face & Eye Tracking and Blink Detection using Event Cameras

Cian Ryan, Brian O Sullivan, Amr Elrasad +4

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 acquir…

cs.CV2020

Learning to Detect Objects with a 1 Megapixel Event Camera

Etienne Perot, Pierre de Tournemire, Davide Nitti +2

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…

cs.CV202067 cited

A Large Scale Event-based Detection Dataset for Automotive

Pierre de Tournemire, Davide Nitti, Etienne Perot +2

We introduce the first very large detection dataset for event cameras. The dataset is composed of more than 39 hours of automotive recordings acquired with a 304x240 ATIS sensor. I…

cs.CV2018

End-to-End Race Driving with Deep Reinforcement Learning

Maximilian Jaritz, Raoul de Charette, Marin Toromanoff +2

We present research using the latest reinforcement learning algorithm for end-to-end driving without any mediated perception (object recognition, scene understanding). The newly pr…