Researchers introduce ShotFinder, a benchmark for open-domain video shot retrieval that includes a three-stage retrieval and localization pipeline. They propose using large language models for query expansion, candidate retrieval, and description-guided shot localization. The benchmark reveals a significant gap to human performance, with challenges in color and visual style localization.