LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training
We present LAION-BVD, a large-scale open video dataset for multimodal learning, which contains 1.3B platform-specific video URLs collected from CommonCrawl. From these, we download 80M videos with a total duration of 10 million hours. The dataset is designed for multimodal pre-training across the video, audio, and image modalities. Using content-aware scene detection, we extract clips for which we synthetically generate video and audio captions. Models trained on these data achieve competitive performance on standard video-text and audio-text benchmarks, with consistent improvements as trainin
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- FuzzySimilar title/name (fuzzy) · 59%Developer-Y/cs-video-courses →
“Fuzzy title match (0.73): “LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimod” ≈ “Developer-Y/cs-video-courses””
- PossiblePossibly related (embedding) · 53%Laion Big Video Dataset →
- LinkedLinked via arxiv author · 85%Andreas Hochlehnert →
“LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training”
- LinkedLinked via arxiv author · 85%Marianna Nezhurina →
“LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training”
- LinkedLinked via arxiv author · 85%Mehdi Cherti →
“LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training”
- LinkedLinked via arxiv author · 85%Andrej Radonjic →
“LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training”
- LinkedLinked via arxiv author · 85%Thaddäus Wiedemer →
“LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training”
- LinkedLinked via arxiv author · 85%Christoph Schuhmann →
“LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training”