Abstract Gaussian Process Latent Variable Model (GPLVM), as a flexible bayesian non-
parametric modeling method, has been extensively studied and applied in many learning …

Cross-modal retrieval has become a highlighted research topic, to provide flexible retrieval
experience across multimedia data such as image, video, text and audio. The core of …

Cross-domain visual data matching is one of the fundamental problems in many real-world
vision tasks, eg, matching persons across ID photos and surveillance videos. Conventional …

End-to-end training from scratch of current deep architectures for new computer vision
problems would require Imagenet-scale datasets, and this is not always possible. In this …

In this paper, we propose a new deep coupled metric learning (DCML) method for cross-
modal matching, which aims to match samples captured from two different modalities (eg …

In this paper we study the problem of content-based image retrieval. In this problem, the
most popular performance measure is the top precision measure, and the most important …

In this article, we investigate the cross-media retrieval between images and text, that is,
using image to search text (I2T) and using text to search images (T2I). Existing cross-media …

Recently, cross-modal search has attracted considerable attention but remains a very
challenging task because of the integration complexity and heterogeneity of the multi-modal …

The heterogeneity-gap between different modalities brings a significant challenge to
multimedia information retrieval. Some studies formalize the cross-modal retrieval tasks as a …

Cross modal (eg, text-to-image or image-to-text) retrieval has received great attention with
the flushed multi-modal social media data. It is of considerable challenge to stride across the …