Poster

Deep Set Prediction Networks

Yan Zhang · Jonathon Hare · Adam Prugel-Bennett

Keywords: Predictive Models Deep Learning Supervised Deep Networks Algorithms -> Structured Prediction; Deep Learning -> Deep Autoencoders; Deep Learning

2019 Poster

[ Paper] [ Poster]

Abstract

Current approaches for predicting sets from feature vectors ignore the unordered nature of sets and suffer from discontinuity issues as a result. We propose a general model for predicting sets that properly respects the structure of sets and avoids this problem. With a single feature vector as input, we show that our model is able to auto-encode point sets, predict the set of bounding boxes of objects in an image, and predict the set of attributes of these objects.

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