Example-Guided Image Synthesis across Arbitrary Scenes using Masked Spatial-Channel Attention and Self-Supervision

Understand

Example-guided image synthesis has recently been attempted to synthesize an image from a semantic label map and an exemplary image.

• In the task, the additional exemplar image provides the style guidance that controls the appearance of the synthesized output.
• Despite the controllability advantage, the existing models are designed on datasets with specific and roughly aligned objects.
• In this paper, we tackle a more challenging and general task, where the exemplar is an arbitrary scene image that is semantically different from the given label map.