The ReC task, or Relation Conversation, introduces a novel approach to understanding object relations in images by unifying text generation, object localization, and relation comprehension. This task challenges models to not only recognize objects within an image but also understand the intricate relationships between them. By training models on the ReC task, researchers can enhance their ability to comprehend visual scenes at a deeper level. This can lead to advancements in various vision-language tasks such as scene graph generation, region captioning, and referring expression comprehension. Additionally, the open-ended nature of the ReC task allows models to generalize better to unseen data and improve their overall performance on complex vision-language tasks.