The article introduces Multi-Stream Scene Script (MTSS), a structured JSON‑based video description paradigm that replaces monolithic captions, explains its design principles, compares its advantages, and presents experimental evidence showing significant gains in both video understanding and generation tasks.
EMNLP 2025 in Suzhou showcases Taobao's booth featuring four cutting‑edge AI papers that introduce a novel embedding compression framework, an automatic iterative refinement method for complex instruction generation, a knowledge infusion scaling law for large language models, and a video caption optimization approach for text‑to‑video generation.
This article presents a comprehensive overview of multimodal video understanding for real-world surveillance, covering task definitions, the new UCA multimodal surveillance dataset, baseline models for video moment localization, captioning, and anomaly detection, experimental results, challenges, and future research directions.
