Collaborative Learning for Extremely Low Bit Asymmetric Hashing

09/25/2018
by   Yadan Luo, et al.
0

Extremely low bit (e.g., 4-bit) hashing is in high demand for retrieval and network compression, yet it could hardly guarantee a manageable convergence or performance due to its severe information loss and shrink of discrete solution space. In this paper, we propose a novel Collaborative Learning strategy for high-quality low-bit deep hashing. The core idea is to distill bit-specific representations for low-bit codes with a group of hashing learners, where hash codes of various length actively interact by sharing and accumulating knowledge. To achieve that, an asymmetric hashing framework with two variants of multi-head embedding structures is derived, termed as Multi-head Asymmetric Hashing (MAH), leading to great efficiency of training and querying. Multiple views from different embedding heads provide supplementary guidance as well as regularization for extremely low bit hashing, hence making convergence faster and more stable. Extensive experiments on three benchmark datasets have been conducted to verify the superiority of the proposed MAH, and show that 8-bit hash codes generated by MAH achieve 94.4 surpasses the performance of 48-bit codes by the state-of-the-arts for image retrieval.

READ FULL TEXT

page 6

page 7

page 8

page 10

research
10/21/2019

Hadamard Codebook Based Deep Hashing

As an approximate nearest neighbor search technique, hashing has been wi...
research
09/17/2020

Deep Momentum Uncertainty Hashing

Discrete optimization is one of the most intractable problems in deep ha...
research
01/25/2018

Dual Asymmetric Deep Hashing Learning

Due to the impressive learning power, deep learning has achieved a remar...
research
03/04/2020

Learning to Hash with Graph Neural Networks for Recommender Systems

Graph representation learning has attracted much attention in supporting...
research
01/20/2015

DeepHash: Getting Regularization, Depth and Fine-Tuning Right

This work focuses on representing very high-dimensional global image des...
research
04/18/2021

HalftimeHash: Modern Hashing without 64-bit Multipliers or Finite Fields

HalftimeHash is a new algorithm for hashing long strings. The goals are ...
research
05/20/2016

Functional Hashing for Compressing Neural Networks

As the complexity of deep neural networks (DNNs) trend to grow to absorb...

Please sign up or login with your details

Forgot password? Click here to reset