code for "S2TD: A Tree-Structured Decoder for Image Paragraph Captioning" accepted by MMAsia 2021
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Updated
Nov 14, 2021 - Python
code for "S2TD: A Tree-Structured Decoder for Image Paragraph Captioning" accepted by MMAsia 2021
Data and code for Kang et al., EMNLP 2019's paper titled "Linguistic Versus Latent Relations for Modeling a Flow in Paragraphs"
A solution to find the best order of random sentences in a paragraph Using Bert algorithm and PyTorch.
Generated image description in the form of coherent paragraphs using Densecap(CNN for Dense Captioning) and Hierarchical RNN and Model was able to perform as good as state-of-art in terms of metrics inclined towards human-like sentences.
Text::KnuthPlass paragraph shaping package for Perl
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