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• W2953116911 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." @default.
• W2953116911 created "2019-06-27" @default.
• W2953116911 creator A5046903577 @default.
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• W2953116911 date "2019-06-15" @default.
• W2953116911 modified "2023-10-18" @default.
• W2953116911 title "Deep Set Prediction Networks" @default.
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