Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction

Understand

Conditional text-to-image generation is an active area of research, with many possible applications.

• Existing research has primarily focused on generating a single image from available conditioning information in one step.
• One practical extension beyond one-step generation is a system that generates an image iteratively, conditioned on ongoing linguistic input or feedback.
• This is significantly more challenging than one-step generation tasks, as such a system must understand the contents of its generated images with respect to the feedback history, the current feedback, as well as the interactions among concepts present in the feedback history.