核心概念
Surprising videos require deep reasoning skills for comprehension.
要約
FunQA dataset focuses on humor, creativity, and magic in videos. It challenges models with tasks like timestamp localization, detailed description, and counter-intuitiveness reasoning. The dataset consists of 4.3K videos and 312K QA pairs. FunMentor enhances VLMs' understanding through multi-turn dialogues.
- Surprising Videos Overview: HumorQA, CreativeQA, MagicQA subsets with specific tasks.
- Introduction to Surprising Videos: Enjoyment based on commonsense violations understanding.
- Data Extraction: Metrics used to evaluate model performance.
- Quotations: None present in the content.
- Inquiry and Critical Thinking:
- How do existing benchmarks differ from FunQA in terms of video types covered?
- What are the limitations of traditional metrics in evaluating free-text tasks?
- How can FunQA dataset be further improved for enhanced video reasoning capabilities?
統計
FunQAは、4.3Kのビデオクリップと312Kの質疑応答ペアから成るデータセットです。
モデルのパフォーマンスを評価するために使用されるメトリクスが含まれています。