Interactive Image Segmentation

Interactive image segmentation aims to efficiently delineate objects within images using minimal user input, such as clicks, scribbles, or lines, to guide a segmentation model. Current research focuses on improving accuracy and reducing user effort through innovative model architectures like transformers and incorporating advanced loss functions, as well as exploring diverse input modalities and efficient algorithms to handle various image types and object complexities. This field is significant for accelerating data annotation in various applications, including medical imaging, remote sensing, and computer vision, ultimately improving the efficiency and scalability of machine learning tasks.