Nov 15, 2017 · In this paper, we propose a new system to discriminatively embed the image and text to a shared visual-textual space. In this field, most ...
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This repository contains the code for our paper Dual-Path Convolutional Image-Text Embedding. Thank you for your kindly attention.
May 22, 2020 · So in a minor contribution, this article constructs an end-to-end dual-path convolutional network to learn the image and text representations.
An end-to-end dual-path convolutional network to learn the image and text representations based on an unsupervised assumption that each image/text group can ...
Better Features. Are the off-the-shelf features good? • Faster Inference Speed. RNN needs wait the former output. • Scalable to Large Datasets.
In this article, we propose a dual-path CNN to simultaneously learn visual and textual representations in an end-to-end fashion, consisting of a deep image CNN ...
This paper builds a convolutional network amenable for fine-tuning the visual and textual representations, where the entire network only contains four ...
Nov 20, 2017 · This paper considers the task of matching images and sentences. The challenge consists in discriminatively embedding the two modalities onto ...
Download the COCO dataset (2014 version) and write the preprocessing code; Write the code for Deep-CNN for image; Write the code for Deep-CNN for text ...
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