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Most of the existing works on image description focus on generatingexpressive descriptions. The only few works that are dedicated to generatingstylish (e.g., romantic, lyric, etc.) descriptions suffer from limited stylevariation and content digression. To address these limitations, we propose acontrollable stylish image description generation model. It can learn togenerate stylish image descriptions that are more related to image content andcan be trained with the arbitrary monolingual corpus without collecting newpaired image and stylish descriptions. Moreover, it enables users to generatevarious stylish descriptions by plugging in style-specific parameters toinclude new styles into the existing model. We achieve this capability via anovel layer normalization layer design, which we will refer to as the DomainLayer Norm (DLN). Extensive experimental validation and user study on variousstylish image description generation tasks are conducted to show thecompetitive advantages of the proposed model.

Unsupervised Stylish Image Description Generation via Domain Layer Norm