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.

View Slides

Extracted Key Phrases

6 Figures and Tables

Citations per Year

54 Citations

Semantic Scholar estimates that this publication has 54 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@inproceedings{Rastegari2013PredictableDH, title={Predictable Dual-View Hashing}, author={Mohammad Rastegari and Jonghyun Choi and Shobeir Fakhraei and Hal Daum{\'e} and Larry S. Davis}, booktitle={ICML}, year={2013} }