A new 19-task video editing benchmark shows that current video LLMs struggle to understand editing concepts, and a model fine-tuned on the benchmark improves both editing and general video reasoning.
Zero-Shot Long-Form Video Understanding through Screenplay
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abstract
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%.
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VEU-Bench: Towards Comprehensive Understanding of Video Editing
A new 19-task video editing benchmark shows that current video LLMs struggle to understand editing concepts, and a model fine-tuned on the benchmark improves both editing and general video reasoning.