Papers › Deep Set Prediction Networks
Deep Set Prediction Networks
Yan Zhang, Jonathon Hare, Adam Prügel-Bennett
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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Syntology Ran 3 of 9 code samples harvested from 1 repository linked to this paper; 6 have no recorded run. Of those that ran: 1 ran · honoured contract; 2 ran · fixture could not drive it.
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Code Syntology ran Syntology
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