Two Stage UNet

Two-stage U-Net architectures are emerging as powerful tools for various image processing tasks, primarily focusing on improving accuracy and efficiency compared to single-stage U-Nets. Research emphasizes incorporating advanced modules like feature interaction and fusion mechanisms, leveraging pre-trained encoders, and integrating semantic segmentation for improved performance in applications such as medical image segmentation and image translation. These advancements are driving progress in diverse fields, including medical imaging analysis, infrared-to-visible image translation, and real-time depth estimation for robotics and autonomous systems.