The fashion industry is on the verge of an unprecedented change. The implementation of
machine learning, computer vision, and artificial intelligence (AI) in fashion applications is …

Out-of-distribution (OOD) detection aims to detect “unknown” data whose labels have not
been seen during the in-distribution (ID) training process. Recent progress in representation …

Fashion is the manner in which we introduce ourselves to the world and has become
perhaps the biggest industry on the planet. In recent years, fashion-related research has …

In recent years, it has become common for consumers to familiarize themselves with the
latest fashion trends through the internet and engage in their own fashion-inspired shopping …

Clothes image search is an important learning task in fashion analysis to find the most
relevant clothes in a database given a user-provided query. To address this problem, most …

Human-object interaction detection that aims at detecting< human, verb, object> triplets is
critical for the holistic human-centric scene understanding. Existing approaches ignore the …

This paper focuses on Information Extraction from Visually Rich Documents, exploring how
deep learning methods are applied in this field. For the purpose of comparing the …

Cross-domain fashion retrieval is a feasible method for finding the required clothing among
a large number of products. Computer vision-based retrieval algorithms have been …

In this paper, we introduce Bangle Fashion Image Retrieval (BangleFIR), a novel dataset
focusing on bangles within the fashion domain. While garment and footwear retrieval has …

Clothes image search is the key technique to effectively search the clothes items that are
most relevant to the query clothes given by the customer. In this work, we propose an Anchor …