Then we introduce a semantic mapper that produces the proxy masks from various input conditions including semantic masks.

In this work, we investigate the task of text-to-image (T2I) synthesis under the abstract-to-intricate setting, i.e., generating intricate visual content from simple

A long standing goal in neuroscience has been to elucidate the functional organization of the brain.

Diffusion models (DMs) have recently gained attention with state-of-the-art performance in text-to-image synthesis.

Advanced image editing is in high demand across a multitude of applications, e.g ., old photo

This process enables the value (feature maps) to be rearranged (through a weighted sum) to align with the form of the query, thereby reflecting their strong correspondence. The input noise is removed because its stochasticity slows down the training. Given the need for balancing between high correspondence and image quality, we empirically set the weights of our loss terms. To demonstrate the influence of the additional losses introduced in our method, we provide both quantitative and qualitative ablations in Figure S2 and S3, respectively. Nonetheless, caution is warranted when overly increasing the number of clusters.