A reinforcement learning agent that controls SAM 2 memory bank updates achieves a +4.91% tracking quality gain over SAM 2 when overfitted per video, indicating untapped potential in memory control.
A N ew A pproach to L inear F iltering and P rediction P roblems, 1960
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SAM2RL: Towards Reinforcement Learning Memory Control in Segment Anything Model 2
A reinforcement learning agent that controls SAM 2 memory bank updates achieves a +4.91% tracking quality gain over SAM 2 when overfitted per video, indicating untapped potential in memory control.