"Learning Graph Convolutional Networks for Multi-Label Recognition and " by Zhaomin Chen, Xiu Shen Wei et al.
The task of multi-label image recognition is to predict a set of object labels that present in an image. As objects normally co-occur in an image, it is desirable to model label dependencies to improve recognition performance. To capture and explore such important information, we propose Graph Convolutional Networks based models for multi-label recognition, where directed graphs are constructed over classes and information is propagated between classes to learn inter-dependent class-level representations. Following this idea, we design two particular models that approach multi-label classifica...
Source: uow.edu.au