RegCL: Compact Continual SAM Adaptation for Visual Grounding in Multi-Sensorial Media
Experiments show that RegCL achieves strong retention and adaptation under domain-incremental learning, outperforming competitive non-replay continual learning and merging baselines, suggesting that RegCL can serve as a compact visual adaptation component for evolving multi-sensorial media pipelines.