Trailer Reimagined: An Innovative, Llm-DRiven, Expressive Automated Movie Summary framework (TRAILDREAMS)
This addresses the challenge of efficient and engaging trailer creation for the film industry, representing an incremental advancement in automated creative processes.
The paper tackles the problem of automating movie trailer production by introducing TRAILDREAMS, a framework that uses a large language model to select visual sequences and dialogues and generate audio elements, resulting in trailers that surpass current state-of-the-art methods in viewer ratings but still fall short compared to human-crafted ones.
This paper introduces TRAILDREAMS, a framework that uses a large language model (LLM) to automate the production of movie trailers. The purpose of LLM is to select key visual sequences and impactful dialogues, and to help TRAILDREAMS to generate audio elements such as music and voiceovers. The goal is to produce engaging and visually appealing trailers efficiently. In comparative evaluations, TRAILDREAMS surpasses current state-of-the-art trailer generation methods in viewer ratings. However, it still falls short when compared to real, human-crafted trailers. While TRAILDREAMS demonstrates significant promise and marks an advancement in automated creative processes, further improvements are necessary to bridge the quality gap with traditional trailers.