Abstract Visual Question Answering (VQA) is a significant cross-disciplinary issue in the
fields of computer vision and natural language processing that requires a computer to output …

In the past few years, cross-modal image-text retrieval (ITR) has experienced increased
interest in the research community due to its excellent research value and broad real-world …

Text-to-image person retrieval aims to identify the target person based on a given textual
description query. The primary challenge is to learn the mapping of visual and textual …

Deep supervised learning has achieved great success in the last decade. However, its
defects of heavy dependence on manual labels and vulnerability to attacks have driven …

Image-text retrieval is a fundamental and vital task in multi-media retrieval and has received
growing attention since it connects heterogeneous data. Previous methods that perform well …

Text-Image Person Re-identification (TIReID) aims to retrieve the image corresponding to
the given text query from a pool of candidate images. Existing methods employ prior …

Cross-modality person re-identification (cm-ReID) is a challenging but key technology for
intelligent video analysis. Existing works mainly focus on learning modality-shared …

Fashion image retrieval based on a query pair of reference image and natural language
feedback is a challenging task that requires models to assess fashion related information …

Text-based person retrieval aims to find the query person based on a textual description.
The key is to learn a common latent space mapping between visual-textual modalities. To …

Text-to-image person re-identification (ReID) aims to search for pedestrian images of an
interested identity via textual descriptions. It is challenging due to both rich intra-modal …