ExchNet: A Unified Hashing Network for Large-Scale Fine-Grained Image Retrieval

by   Quan Cui, et al.
Waseda University
Nanjing University

Retrieving content relevant images from a large-scale fine-grained dataset could suffer from intolerably slow query speed and highly redundant storage cost, due to high-dimensional real-valued embeddings which aim to distinguish subtle visual differences of fine-grained objects. In this paper, we study the novel fine-grained hashing topic to generate compact binary codes for fine-grained images, leveraging the search and storage efficiency of hash learning to alleviate the aforementioned problems. Specifically, we propose a unified end-to-end trainable network, termed as ExchNet. Based on attention mechanisms and proposed attention constraints, it can firstly obtain both local and global features to represent object parts and whole fine-grained objects, respectively. Furthermore, to ensure the discriminative ability and semantic meaning's consistency of these part-level features across images, we design a local feature alignment approach by performing a feature exchanging operation. Later, an alternative learning algorithm is employed to optimize the whole ExchNet and then generate the final binary hash codes. Validated by extensive experiments, our proposal consistently outperforms state-of-the-art generic hashing methods on five fine-grained datasets, which shows our effectiveness. Moreover, compared with other approximate nearest neighbor methods, ExchNet achieves the best speed-up and storage reduction, revealing its efficiency and practicality.


page 1

page 2

page 3

page 4


Cascading Hierarchical Networks with Multi-task Balanced Loss for Fine-grained hashing

With the explosive growth in the number of fine-grained images in the In...

Cross-Scale Context Extracted Hashing for Fine-Grained Image Binary Encoding

Deep hashing has been widely applied to large-scale image retrieval task...

Feature Pyramid Hashing

In recent years, deep-networks-based hashing has become a leading approa...

ShadingNet: Image Intrinsics by Fine-Grained Shading Decomposition

In general, intrinsic image decomposition algorithms interpret shading a...

Simultaneous Region Localization and Hash Coding for Fine-grained Image Retrieval

Fine-grained image hashing is a challenging problem due to the difficult...

SEMICON: A Learning-to-hash Solution for Large-scale Fine-grained Image Retrieval

In this paper, we propose Suppression-Enhancing Mask based attention and...

Deep Region Hashing for Efficient Large-scale Instance Search from Images

Instance Search (INS) is a fundamental problem for many applications, wh...

Code Repositories



view repo

Please sign up or login with your details

Forgot password? Click here to reset