Learning an event sequence embedding for event-based deep stereo
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Event cameras are bioinspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have a very high dynamic range, which enables them to provide reliable visual inf ...
Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have a very high dynamic range, which enables them to provide reliable visual in ...
Institute of Electrical and Electronics Engineers2018
Event cameras are novel, bio-inspired visual sensors, whose pixels output asynchronous and independent times-tamped spikes at local intensity changes, called ‘events’. Event cameras offer advantages over conventional frame-based cameras in terms of latency ...
Event cameras are novel bio-inspired vision sensors that output pixel-level intensity changes, called “events”, instead of traditional video images. These asynchronous sensors naturally respond to motion in the scene with very low latency (in the order of ...
Event cameras are revolutionary sensors that work radically differently from standard cameras. Instead of capturing intensity images at a fixed rate, event cameras measure changes of intensity asynchronously, in the form of a stream of events, which encode ...
We present a unifying framework to solve several computer vision problems with event cameras: motion, depth and optical flow estimation. The main idea of our framework is to find the point trajectories on the image plane that are best aligned with the even ...
Accurate 3D human pose estimation from single images is possible with sophisticated deep-net architectures that have been trained on very large datasets. However, this still leaves open the problem of capturing motions for which no such database exists. Ma ...
Accurate 3D human pose estimation from single images is possible with sophisticated deep-net architectures that have been trained on very large datasets. However, this still leaves open the problem of capturing motions for which no such database exists. Ma ...
