HourVideo: 1-Hour Video-Language Understanding

1-hour videos and v1.0 development set annotations for long-form video-language understanding. This benchmark from Stanford University was introduced at NeurIPS 2024 to evaluate models on extended temporal sequences.

Use Cases

• Evaluate long-form video-language models using the v1.0 development set annotations
• Train multimodal systems using the captions associated with 1-hour videos
• Benchmark temporal reasoning across 1-hour video sequences

Strengths

• 1-hour video durations for long-context temporal reasoning
• v1.0 development set annotations for model evaluation
• Captions provided for video-language alignment tasks