Our work “Leveraging Synthetic Data to Learn Video Stabilization Under Adverse Conditions” was presented at the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2024). Our paper presents a new technique that is trained on synthetic data in order to perform video stabilisation (on real videos). In particular, our approach also performs well under adverse weather conditions, since it does not rely on the usual feature extraction techniques. The paper is available here. Our code and datasets are also available.