Jethro's Braindump

Cross-modal Hashing

Cross-modal hashing is the compression of high dimensional data into compact binary codes with similar binary codes for similar objects. The key ideas is to create codes for cross-modal retrieval. The constraints are :

  1. It has to be an N-dimensional hamming space – a binary representation with a controllable number of bits.
  2. The same object from different modalities has to have a similar hash code
  3. The space has to be similarity-preserving

(Baltruv saitis, Ahuja, and Morency 2017) has some good reference papers.

Bibliography

Baltruv saitis, Tadas, Chaitanya Ahuja, and Louis-Philippe Morency. 2017. “Multimodal Machine Learning: A Survey and Taxonomy.” CoRR.