Hadamard Codebook Based Deep Hashing

Understand

As an approximate nearest neighbor search technique, hashing has been widely applied in large-scale image retrieval due to its excellent efficiency.

• Most supervised deep hashing methods have similar loss designs with embedding learning, while quantizing the continuous high-dim feature into compact binary space.
• We argue that the existing deep hashing schemes are defective in two issues that seriously affect the performance, i.e., bit independence and bit balance.
• The former refers to hash codes of different classes should be independent of each other, while the latter means each bit should have a balanced distribution of +1s and -1s.