Abstract: Embodiments described herein provide a method for autonomous agents (which may be situated, embodied agents) to learn new visual objects, and recognize the same objects within the same “runtime”/session/interaction, and be able to train a longer-term visual memory model on the object. A visual memory system stores templates of objects and compares images to these templates. An internal or external (to the agent) signal may determine which object/s to compare. The visual memory system stores new and unrecognized objects as “templates” and returns whether or not any region of the image is likely to contain a match for any of the stored templates. There is thus provided one-shot visual learning.