Segmentation Mask

Segmentation masks are digital representations of object boundaries within images, crucial for various computer vision tasks. Current research focuses on improving the accuracy and efficiency of generating these masks, particularly in low-data regimes, exploring methods like data augmentation, model re-adaptation, and the utilization of foundation models such as SAM (Segment Anything Model) and diffusion models. These advancements are significantly impacting fields like medical imaging, autonomous driving, and agricultural technology by enabling automated analysis and improved decision-making in data-scarce or complex scenarios.