Live Interactive Training for Video Segmentation
Interactive video segmentation often requires many user corrections, but existing models like SAM2 don't learn from this feedback. This paper introduces Live Interactive Training (LIT), a method that allows models to learn online at inference time by updating a small adapter module instantly when users correct an error. LIT-LoRA significantly reduces the number of required user corrections without needing heavy training.