A Comprehensive Survey of Deep Learning for Image Captioning
نویسندگان
چکیده
منابع مشابه
Deep Learning for Automatic Image Captioning in Poor Training Conditions
English. Recent advancements in Deep Learning show that the combination of Convolutional Neural Networks and Recurrent Neural Networks enables the definition of very effective methods for the automatic captioning of images. Unfortunately, this straightforward result requires the existence of large-scale corpora and they are not available for many languages. This paper describes a simple methodo...
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Image captioning, a popular topic in computer vision, has achieved substantial progress in recent years. However, the distinctiveness of natural descriptions is often overlooked in previous work. It is closely related to the quality of captions, as distinctive captions are more likely to describe images with their unique aspects. In this work, we propose a new learning method, Contrastive Learn...
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The existing image captioning approaches typically train a one-stage sentence decoder, which is difficult to generate rich fine-grained descriptions. On the other hand, multi-stage image caption model is hard to train due to the vanishing gradient problem. In this paper, we propose a coarse-to-fine multistage prediction framework for image captioning, composed of multiple decoders each of which...
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Recently, much advance has been made in image captioning, and an encoder-decoder framework has achieved outstanding performance for this task. In this paper, we propose an extension of the encoder-decoder framework by adding a component called guiding network. The guiding network models the attribute properties of input images, and its output is leveraged to compose the input of the decoder at ...
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ژورنال
عنوان ژورنال: ACM Computing Surveys
سال: 2019
ISSN: 0360-0300,1557-7341
DOI: 10.1145/3295748