This project is a foundation model and research toolkit designed for promptable object segmentation and temporal tracking. It provides a unified framework for isolating specific regions or objects within both static images and dynamic video sequences.
The system distinguishes itself through a streaming memory architecture that maintains temporal consistency by storing and retrieving object features across frames. This mechanism allows the model to resolve occlusions and preserve object identity even when targets move out of view or change appearance. By utilizing a shared backbone for both image and video inputs, the model ensures consistent performance across diverse visual data types.
The toolkit supports a broad range of computer vision tasks, including the generation of precise visual boundaries through user-provided spatial prompts and the refinement of models on specialized datasets. It is structured to facilitate custom training and analysis, enabling the extraction of objects from visual streams for further processing.
