Authors: Ranjan Akarsh
This paper depicts a network called LeGuess (LeG) which, using computer vision, is able to precisely predict the future scenes given sequence of images. The network is able to automatically learn the features and representations of the objects present in the sequence of images fed as input. Furthermore, this network learns the movements of the objects and predicts very well. The network is mainly designed for the domain of Autonomous Vehicles, which contains plenty of applications alone. Taking this in note, LeG can be applied to predict the steering angles, predicting the future positions of cars, trucks, cyclists, etc., ready a generative model to generate images along with steering angles, which could be used to train vehicles to drive, as well as generate images of road with/without lane to train segmentation for better autonomous driving. The network is designed to make predictions (local) of up to given number of time-steps ahead.
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[v1] 2020-01-04 09:21:59
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