The IntentVC Challenge tackles a fundamental limitation in video captioning by introducing user-controllable, intention-oriented outputs. Video understanding is a crucial task in that the ultimate goal is to capture everything happening in a video, and it is not the state of the ideal performance in the existing literature. Unlike traditional approaches that generate general-purpose, one-size-fits-all descriptions of videos, this challenge enables captions tailored to specific user-defined intentions that can test video understanding modules in capturing various aspects of the video. The distinction is crucial for improving accessibility, personalization, and adaptability in multimedia applications. General video descriptions, such as the Non-Intention-Oriented example in Figure(a), offer a broad overview of the video content but lack the specificity to address particular user needs. In contrast, Intention-Oriented Controllable captions (Figures(b, c)) allow for targeted focus on specific objects, actions, or contexts within the video, enabling greater flexibility and relevance.