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 …

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 …

Abstract Object Re-identification (Re-ID) aims to identify specific objects across different
times and scenes, which is a widely researched task in computer vision. For a prolonged …

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 …

Text-based person retrieval is a challenging task that aims to search pedestrian images with
the same identity according to language descriptions. Current methods usually …

In this paper, we introduce a large Multi-Attribute and Language Search dataset for text-
based person retrieval, called MALS, and explore the feasibility of performing pre-training on …

Abstract Large-scale Vision-and-Language (V+ L) pre-training for representation learning
has proven to be effective in boosting various downstream V+ L tasks. However, when it …

Text-to-image person re-identification (TIReID) is a compelling topic in the cross-modal
community which aims to retrieve the target person based on a textual query. Although …

Text-based person search aims to associate pedestrian images with natural language
descriptions. In this task, extracting differentiated representations and aligning them among …