Multi-label Image Classification using Adaptive Graph Convolutional Networks: from a Single Domain to Multiple Domains

01/11/2023
by   Indel Pal Singh, et al.
0

This paper proposes an adaptive graph-based approach for multi-label image classification. Graph-based methods have been largely exploited in the field of multi-label classification, given their ability to model label correlations. Specifically, their effectiveness has been proven not only when considering a single domain but also when taking into account multiple domains. However, the topology of the used graph is not optimal as it is pre-defined heuristically. In addition, consecutive Graph Convolutional Network (GCN) aggregations tend to destroy the feature similarity. To overcome these issues, an architecture for learning the graph connectivity in an end-to-end fashion is introduced. This is done by integrating an attention-based mechanism and a similarity-preserving strategy. The proposed framework is then extended to multiple domains using an adversarial training scheme. Numerous experiments are reported on well-known single-domain and multi-domain benchmarks. The results demonstrate that our approach outperforms the state-of-the-art in terms of mean Average Precision (mAP) and model size.

READ FULL TEXT

page 1

page 5

page 6

page 8

page 9

page 10

page 12

research
04/07/2019

Multi-Label Image Recognition with Graph Convolutional Networks

The task of multi-label image recognition is to predict a set of object ...
research
09/28/2019

Learning Category Correlations for Multi-label Image Recognition with Graph Networks

Multi-label image recognition is a task that predicts a set of object la...
research
12/26/2019

Multi-Label Graph Convolutional Network Representation Learning

Knowledge representation of graph-based systems is fundamental across ma...
research
03/08/2022

Graph Attention Transformer Network for Multi-Label Image Classification

Multi-label classification aims to recognize multiple objects or attribu...
research
04/08/2022

Bag-of-Words vs. Sequence vs. Graph vs. Hierarchy for Single- and Multi-Label Text Classification

Graph neural networks have triggered a resurgence of graph-based text cl...
research
07/26/2017

Graph-Based Classification of Omnidirectional Images

Omnidirectional cameras are widely used in such areas as robotics and vi...
research
09/14/2022

Combining Metric Learning and Attention Heads For Accurate and Efficient Multilabel Image Classification

Multi-label image classification allows predicting a set of labels from ...

Please sign up or login with your details

Forgot password? Click here to reset