  Multi-modal generation has been widely explored in recent years. Current
research directions involve generating text based on an image or vice versa. In
this paper, we propose a new task called CIGLI: Conditional Image Generation
from Language and Image. Instead of generating an image based on text as in
text-image generation, this task requires the generation of an image from a
textual description and an image prompt. We designed a new dataset to ensure
that the text description describes information from both images, and that
solely analyzing the description is insufficient to generate an image. We then
propose a novel language-image fusion model which improves the performance over
two established baseline methods, as evaluated by quantitative (automatic) and
qualitative (human) evaluations. The code and dataset is available at
https://github.com/vincentlux/CIGLI.
