Recent years have witnessed the fast development of large-scale pre-training frameworks
that can extract multi-modal representations in a unified form and achieve promising …

Cross-modal retrieval methods are the preferred tool to search databases for the text that
best matches a query image and vice versa However, image-text retrieval models commonly …

With the exponential surge in diverse multi-modal data, traditional uni-modal retrieval
methods struggle to meet the needs of users demanding access to data from various …

Pre-trained vision-language models like CLIP have recently shown superior performances
on various downstream tasks, including image classification and segmentation. However, in …

In the fashion domain, there exists a variety of vision-and-language (V+ L) tasks, including
cross-modal retrieval, text-guided image retrieval, multi-modal classification, and image …

Abstract The advancement of Zero-Shot Learning in the medical domain has been driven
forward by using pre-trained models on large-scale image-text pairs focusing on image-text …

Fashion vision-language pre-training models have shown efficacy for a wide range of
downstream tasks. However, general vision-language pre-training models pay less attention …

Image aesthetics assessment (IAA) aims at predicting the aesthetic quality of images.
Recently, large pre-trained vision-language models, like CLIP, have shown impressive …

Research connecting text and images has recently seen several breakthroughs, with models
like CLIP, DALL* E 2, and Stable Diffusion. However, the connection between text and other …

Advances in self-supervised learning, especially in contrastive learning, have drawn
attention to investigating these techniques in providing effective visual representations from …