Multimodal Region-level Clothing Re-identification in E-commerce Livestreaming

• Multimodal classification results surpasses the state-of-the-art methods.
• Works ...

In this paper, a graph-based, supervised classification method for multimodal data is introduced. It can be applied on data of any type consisting of any number of modalities and can also be used for the classification of datasets with ...

The purpose of multimodal classification is to integrate features from diverse information sources to make decisions. The interactions between different modalities are crucial to this task. However, common strategies in previous studies have been ...

• A unified network for image-text matching and classification.
• Seamlessly incorporating the matching and classification components.
• A multi-stage training algorithm by combining the matching and classification loss.
• ...

Multimodal learning has been an important and challenging problem for decades, which aims to bridge the modality gap between heterogeneous representations, such as vision and language. Unlike many current approaches which only focus on either ...