DeepAI AI Chat
Log In Sign Up

TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval

by   Yongbiao Chen, et al.

Deep hamming hashing has gained growing popularity in approximate nearest neighbour search for large-scale image retrieval. Until now, the deep hashing for the image retrieval community has been dominated by convolutional neural network architectures, e.g. <cit.>. In this paper, inspired by the recent advancements of vision transformers, we present Transhash, a pure transformer-based framework for deep hashing learning. Concretely, our framework is composed of two major modules: (1) Based on Vision Transformer (ViT), we design a siamese vision transformer backbone for image feature extraction. To learn fine-grained features, we innovate a dual-stream feature learning on top of the transformer to learn discriminative global and local features. (2) Besides, we adopt a Bayesian learning scheme with a dynamically constructed similarity matrix to learn compact binary hash codes. The entire framework is jointly trained in an end-to-end manner. To the best of our knowledge, this is the first work to tackle deep hashing learning problems without convolutional neural networks (CNNs). We perform comprehensive experiments on three widely-studied datasets: CIFAR-10, NUSWIDE and IMAGENET. The experiments have evidenced our superiority against the existing state-of-the-art deep hashing methods. Specifically, we achieve 8.2%, 2.6%, 12.7% performance gains in terms of average mAP for different hash bit lengths on three public datasets, respectively.


page 3

page 6

page 8


Vision Transformer Hashing for Image Retrieval

Deep learning has shown a tremendous growth in hashing techniques for im...

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

In this paper, we make the very first attempt to investigate the integra...

Query-adaptive Image Retrieval by Deep Weighted Hashing

Hashing methods have attracted much attention for large scale image retr...

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...

Transfer Adversarial Hashing for Hamming Space Retrieval

Hashing is widely applied to large-scale image retrieval due to the stor...

Random VLAD based Deep Hashing for Efficient Image Retrieval

Image hash algorithms generate compact binary representations that can b...

Deep Multi-View Enhancement Hashing for Image Retrieval

Hashing is an efficient method for nearest neighbor search in large-scal...