  Personality image captioning (PIC) aims to describe an image with a natural
language caption given a personality trait. In this work, we introduce a novel
formulation for PIC based on a communication game between a speaker and a
listener. The speaker attempts to generate natural language captions while the
listener encourages the generated captions to contain discriminative
information about the input images and personality traits. In this way, we
expect that the generated captions can be improved to naturally represent the
images and express the traits. In addition, we propose to adapt the language
model GPT2 to perform caption generation for PIC. This enables the speaker and
listener to benefit from the language encoding capacity of GPT2. Our
experiments show that the proposed model achieves the state-of-the-art
performance for PIC.
