DeepAI AI Chat
Log In Sign Up

DVHN: A Deep Hashing Framework for Large-scale Vehicle Re-identification

by   Yongbiao Chen, et al.

In this paper, we make the very first attempt to investigate the integration of deep hash learning with vehicle re-identification. We propose a deep hash-based vehicle re-identification framework, dubbed DVHN, which substantially reduces memory usage and promotes retrieval efficiency while reserving nearest neighbor search accuracy. Concretely, DVHN directly learns discrete compact binary hash codes for each image by jointly optimizing the feature learning network and the hash code generating module. Specifically, we directly constrain the output from the convolutional neural network to be discrete binary codes and ensure the learned binary codes are optimal for classification. To optimize the deep discrete hashing framework, we further propose an alternating minimization method for learning binary similarity-preserved hashing codes. Extensive experiments on two widely-studied vehicle re-identification datasets- VehicleID and VeRi- have demonstrated the superiority of our method against the state-of-the-art deep hash methods. DVHN of 2048 bits can achieve 13.94% and 10.21% accuracy improvement in terms of mAP and Rank@1 for VehicleID (800) dataset. For VeRi, we achieve 35.45% and 32.72% performance gains for Rank@1 and mAP, respectively.


page 1

page 3

page 8

page 9

page 10


Deep Supervised Discrete Hashing

With the rapid growth of image and video data on the web, hashing has be...

Compact Hash Code Learning with Binary Deep Neural Network

In this work, we firstly propose deep network models and learning algori...

TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval

Deep hamming hashing has gained growing popularity in approximate neares...

Hadamard Codebook Based Deep Hashing

As an approximate nearest neighbor search technique, hashing has been wi...

A Revisit on Deep Hashings for Large-scale Content Based Image Retrieval

There is a growing trend in studying deep hashing methods for content-ba...

From Hashing to CNNs: Training BinaryWeight Networks via Hashing

Deep convolutional neural networks (CNNs) have shown appealing performan...

Learning to Rank Binary Codes

Binary codes have been widely used in vision problems as a compact featu...