Abstract We introduce the Segment Anything (SA) project: a new task, model, and dataset for
image segmentation. Using our efficient model in a data collection loop, we built the largest …

We present Segment Anything Model 2 (SAM 2), a foundation model towards solving
promptable visual segmentation in images and videos. We build a data engine, which …

Abstract The recent Segment Anything Model (SAM) represents a big leap in scaling up
segmentation models, allowing for powerful zero-shot capabilities and flexible prompting …

While semantic segmentation has seen tremendous improvements in the past, there are still
significant labeling efforts necessary and the problem of limited generalization to classes …

Automated animal face identification plays a crucial role in the monitoring of behaviors,
conducting of surveys, and finding of lost animals. Despite the advancements in human face …

Segment anything model (SAM) is a promising prompt-guided vision foundation model to
segment objects of interest. However, the extensive computational requirements of SAM …

This paper introduces SeaTurtleID, the first public large-scale, long-span dataset with sea
turtle photographs captured in the wild. The dataset is suitable for benchmarking re …

Abstract Segment Anything Model (SAM) has emerged as a transformative approach in
image segmentation acclaimed for its robust zero-shot segmentation capabilities and …

The capabilities of foundation models most recently the Segment Anything Model have
gathered a large degree of attention for providing a versatile framework for tackling a wide …

This paper introduces the first public large-scale, long-span dataset with sea turtle
photographs captured in the wild-SeaTurtleID2022. The dataset contains 8729 photographs …