We introduced a combined strategy that integrates fine-tuning a foundation model on our synthetic dataset and a non-learning method to focus on the interesting areas, enabling high-quality segmentation masks on unseen data.
We evaluated our segmentation model on out-of-domain data, achieving promising and accurate segmentation results with minimal artifacts.
