With the urgent demand for generalized deep models, many pre-trained big models are
proposed, such as bidirectional encoder representations (BERT), vision transformer (ViT) …

Transformer is a promising neural network learner, and has achieved great success in
various machine learning tasks. Thanks to the recent prevalence of multimodal applications …

Unsupervised large-scale vision-language pre-training has shown promising advances on
various downstream tasks. Existing methods often model the cross-modal interaction either …

In recent times, artificial intelligence (AI) has been generating a significant impact in various
industry sectors, which implies that companies must be ready to adjust to this promising start …

Abstract Vision-Language Pre-training (VLP) models have shown remarkable performance
on various downstream tasks. Their success heavily relies on the scale of pre-trained cross …

Abstract Vision-Language Pretraining (VLP) has shown impressive results on diverse
downstream tasks by offline training on large-scale datasets. Regarding the growing nature …

The remarkable success of transformers in the field of natural language processing has
sparked the interest of the speech-processing community, leading to an exploration of their …

Abstract recommendation, and marketing services. Extensive efforts have been made to
conquer the cross-modal retrieval problem in the general domain. When it comes to E …

Despite the potential of multi-modal pre-training to learn highly discriminative feature
representations from complementary data modalities, current progress is being slowed by …

Given a query composed of a reference image and a relative caption, the Composed Image
Retrieval goal is to retrieve images visually similar to the reference one that integrates the …