With the recent advances of neural models and natural language processing,
automatic generation of classical Chinese poetry has drawn significant
attention due to its artistic and cultural value. Previous works mainly focus
on generating poetry given keywords or other text information, while visual
inspirations for poetry have been rarely explored...
Generating poetry from
images is much more challenging than generating poetry from text, since images
contain very rich visual information which cannot be described completely using
several keywords, and a good poem should convey the image accurately. In this
paper, we propose a memory based neural model which exploits images to generate
poems. Specifically, an Encoder-Decoder model with a topic memory network is
proposed to generate classical Chinese poetry from images. To the best of our
knowledge, this is the first work attempting to generate classical Chinese
poetry from images with neural networks. A comprehensive experimental
investigation with both human evaluation and quantitative analysis demonstrates
that the proposed model can generate poems which convey images accurately.