This monograph surveys vision-language pre-training (VLP) methods for multimodal
intelligence that have been developed in the last few years. We group these approaches …

This review explores the integration of enhanced personalization and seamless multimodal
interfaces in the field of fashion design and recommendation. We examine the increasing …

Abstract In Composed Image Retrieval (CIR), a user combines a query image with text to
describe their intended target. Existing methods rely on supervised learning of CIR models …

We propose a Vision-Language Transformer (VLT) framework for referring segmentation to
facilitate deep interactions among multi-modal information and enhance the holistic …

Composed Image Retrieval (CoIR) has recently gained popularity as a task that considers
both text and image queries together, to search for relevant images in a database. Most …

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 …

Two primary input modalities prevail in image retrieval: sketch and text. While text is widely
used for inter-category retrieval tasks sketches have been established as the sole preferred …

Image-text retrieval is a fundamental task to bridge vision and language by exploiting
various strategies to fine-grained alignment between regions and words. This is still tough …

Chats emerge as an effective user-friendly approach for information retrieval, and are
successfully employed in many domains, such as customer service, healthcare, and finance …

Composed image retrieval (CIR) is a new and flexible image retrieval paradigm, which can
retrieve the target image for a multimodal query, including a reference image and its …