Predictable Dual-View Hashing

We propose a Predictable Dual-View Hashing (PDH) algorithm which embeds proximity of data samples in the original spaces. We create a cross-view hamming space with the ability to compare information from previously incomparable domains with a notion of ‘predictability’. By performing comparative experimental analysis on two large datasets, PASCAL-Sentence and SUN-Attribute, we demonstrate the superiority of our method to the state-of-the-art dual-view binary code learning algorithms.

Authors

• Mohammad Rastegari
• Jonghyun Choi
• Shobeir Fakhraei
• Hal Daumé III
• Larry S. Davis

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