[R] Heidelberg University Researchers Combine CNNs and Transformers to Synthesize High-Resolution Images

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Is there a way to efficiently code inductive image biases into models while retaining all the flexibility of transformers? “Yes,” say researchers from Germany’s Heidelberg University. In a new paper, the team proposes a novel approach that combines the effectiveness of the inductive bias in convolutional neural networks (CNNs) with the expressivity of transformers to model and synthesize high resolution images.

Here is a quick read: Heidelberg University Researchers Combine CNNs and Transformers to Synthesize High-Resolution Images

The paper Taming Transformers for High-Resolution Image Synthesis is on arXiv. This project is also on GitHub.

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