Using synthetic datasets like GTA-HDR for computer vision tasks beyond HDR image reconstruction has several implications. Firstly, the availability of large-scale synthetic datasets like GTA-HDR enables researchers to train and evaluate computer vision models in a controlled environment with diverse and realistic scenes. This can lead to more robust and generalizable models that perform well across different scenarios. Secondly, synthetic datasets provide a cost-effective and scalable solution for data collection, especially in scenarios where collecting real-world data is challenging or expensive. This allows researchers to explore a wide range of applications and scenarios without the constraints of real-world data limitations. Additionally, synthetic datasets like GTA-HDR can be used to augment existing datasets, providing additional training data to improve the performance of computer vision models. Overall, the findings from GTA-HDR demonstrate the potential of synthetic datasets in advancing research in computer vision tasks beyond HDR image reconstruction.