  The Long-form Video Question-Answering task requires the comprehension and
analysis of extended video content to respond accurately to questions by
utilizing both temporal and contextual information. In this paper, we present
MM-Screenplayer, an advanced video understanding system with multi-modal
perception capabilities that can convert any video into textual screenplay
representations. Unlike previous storytelling methods, we organize video
content into scenes as the basic unit, rather than just visually continuous
shots. Additionally, we developed a ``Look Back'' strategy to reassess and
validate uncertain information, particularly targeting breakpoint mode.
MM-Screenplayer achieved highest score in the CVPR'2024 LOng-form VidEo
Understanding (LOVEU) Track 1 Challenge, with a global accuracy of 87.5% and a
breakpoint accuracy of 68.8%.
