SAM2 Adapter

SAM2-Adapter research focuses on improving the performance and adaptability of the Segment Anything Model 2 (SAM2), a powerful foundation model for image and video segmentation, particularly in challenging domains like medical imaging and video object segmentation. Current research emphasizes developing efficient adapter modules that leverage SAM2's pre-trained weights while incorporating task-specific knowledge, often through parameter-efficient fine-tuning or other lightweight adaptation techniques. This work aims to bridge the performance gap between SAM2 and state-of-the-art methods in specific applications, reducing the need for extensive retraining and enabling broader use of this powerful model in diverse fields.