edges2shoes
edges2shoes is a dataset and task used in image-to-image translation research, focusing on converting edge-based representations into photorealistic shoe images. It was introduced as part of the pix2pix framework to illustrate conditional adversarial networks’ ability to translate one domain into another. The dataset comprises paired samples: an edge map or sketch of a shoe and the corresponding real photograph of that shoe. These pairs enable supervised training of models that learn to map simple outlines to detailed color images.
In typical setups, a conditional generative adversarial network is trained with a U-Net style generator and
Uses and evaluations of edges2shoes center on demonstrating image-to-image translation capabilities and benchmarking model performance on
Limitations include the dataset’s domain specificity to shoes, potential biases in photography and styling, and the