Weakly supervised image classification and pointwise localization with graph convolutional networks

作者：

Highlights：

• A new deep learning framework is proposed in this paper, which can leverage the object label inter-dependent for weakly supervised learning.

• We creatively introduce a novel initialization method of label embeddings for inter-relationships learning.

• Ablation studies of our model are provided in detail.

• Our models can be applied to object classification and weakly supervised pointwise object localization.

摘要

•A new deep learning framework is proposed in this paper, which can leverage the object label inter-dependent for weakly supervised learning.•We creatively introduce a novel initialization method of label embeddings for inter-relationships learning.•Ablation studies of our model are provided in detail.•Our models can be applied to object classification and weakly supervised pointwise object localization.

论文关键词：Deep learning,Learning systems,Convolutional neural networks,Predictive models,Image classification,Graph theory

论文评审过程：Received 30 October 2019, Revised 4 April 2020, Accepted 15 August 2020, Available online 15 August 2020, Version of Record 21 August 2020.

论文官网地址：https://doi.org/10.1016/j.patcog.2020.107596