Apr 1, 2020 · In this paper, we present a novel Graph Structured Matching Network (GSMN) to learn fine-grained correspondence.

In this paper, we propose a graph structured matching network for image-text matching, which performs match- ing on heterogeneous visual and textual graphs.

This is Graph Structured Network for Image-Text Matching, source code of GSMN (project page). The paper is accepted by CVPR2020. It is built on top of the SCAN ...

In this paper, we present a novel Graph Structured Matching Network (GSMN) to learn fine-grained correspondence.

In this paper, we propose a graph structured matching network for image-text matching, which performs match- ing on heterogeneous visual and textual graphs.

The GSMN explicitly models object, relation and attribute as a structured phrase, which not only allows to learn correspondence of object, relation and ...

Papertalk is an open-source platform where scientists share video presentations about their newest scientific results - and watch, like + discuss them.

In this paper, we propose a novel Dual Revised Semantic Graph Structured Network (DRSGN) to supplement global supervision to the regional semantics adaptively ...

Image-text matching is a challenging task in cross-modal learning due to the discrepancy of data representation between different modalities of images and texts ...

Apr 1, 2020 · This paper presents a novel Graph Structured Matching Network (GSMN) to learn fine-grained correspondence of structured phrase correspondence.