Per-feature gating based on distribution distance enables better control in unpaired image translation, letting you preserve important structures while achieving realistic style changes without retraining.
PRISM is a new method for changing images from one style to another (like turning day photos into night) without paired training examples. Instead of using a single global control value, it learns a per-feature gate based on how far each image feature is from the target style, allowing precise control over what changes and what stays the same.