Emoji Kitchen with Controlled Fusion
Keywords: Image fusion, generative model, diffusion model
TL;DR: Proposing a new image fusion model that can balance details and semantic features.
Abstract: The image fusion method is widely used in many different fields. The fusion processes both need models to extract semantic information and contain details. Traditional image processing techniques used for this issue have limited ability to extract semantic features from images, and advanced deep learning techniques often lose the details. In this work, we propose the Controlled Fusion Network (CFN) that adopts a multi-step progressive generation method and injects control elements at every step. We test the model in the emoji fusion task which accepts various emojis and combines them. We find that the generated emojis sufficiently retain and reasonably combine the semantic information of the input images, while the result images also conform to human intuitive perception. Our source code is released at: https://github.com/ChengAoShen/Emoji_fusion.
Submission Number: 19
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