[GQN] Neural Scene Representation and Rendering | AISC

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Canada LLMs Explained - Aggregate Intellect - AI.SCIENCE
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Published on ● Video Link: https://www.youtube.com/watch?v=XJnuEO59XfQ


Duration: 1:30:57
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For more info, including the slides, paper, link to code and datasets see

https://aisc.a-i.science/events/2019-03-25/

abstract:
Scene representation – the process of converting visual sensory data into concise descriptions – is a requirement for intelligent behaviour. Recent work has shown that neural networks excel at
this task when provided large labelled datasets. However, removing the reliance on human labelling remains an important open problem. To this end, we introduce the Generative Query Network (GQN), a framework within which machines learn to represent scenes using only their own sensors. The GQN takes as input images of a scene taken from different viewpoints, constructs an internal representation, and uses this representation to predict the appearance of that scene from previously unobserved viewpoints. The GQN demonstrates representation learning without human labels or domain knowledge, paving the way towards machines that autonomously learn to understand the world around them



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Tags:
deep learning
machine learning
deep mind
gqn