Image captioning, also called report generation in medical field, aims to describe visual
content of images in human language, which requires to model semantic relationship …

Object detection is a fundamental but challenging issue in the field of generic image
analysis; it plays an important role in a wide range of applications and has been receiving …

The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

From the beginning of zero-shot learning research, visual attributes have been shown to
play an important role. In order to better transfer attribute-based knowledge from known to …

Facial expression recognition in the wild is challenging due to various unconstrained
conditions. Although existing facial expression classifiers have been almost perfect on …

Recent work in domain adaptation bridges different domains by adversarially learning a
domain-invariant representation that cannot be distinguished by a domain discriminator …

Automatically generating language descriptions of remote sensing images has become an
emerging research hot spot in the remote sensing field. Attention-based captioning, as a …

As one of the most fundamental techniques in multimodal learning, cross-modal matching
aims to project various sensory modalities into a shared feature space. To achieve this …

We propose Visual News Captioner, an entity-aware model for the task of news image
captioning. We also introduce Visual News, a large-scale benchmark consisting of more …

The encoder–decoder framework is prevalent in existing remote-sensing image captioning
(RSIC) models. The appearance of attention mechanisms brings significant results …