I2I Translation

Image-to-image (I2I) translation aims to transform images from one domain to another, a crucial task with applications across diverse fields. Current research focuses on improving the quality and consistency of translations, particularly in unpaired settings where corresponding images aren't available, using models like Generative Adversarial Networks (GANs) and diffusion models enhanced with techniques such as contrastive learning and cycle consistency. These advancements are driving progress in areas like remote sensing, medical imaging, and artistic style transfer by enabling more accurate and realistic image manipulations.