LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training

• URL: http://arxiv.org/abs/2608.24845v1
• Date: Tue, 25 Aug 2026 17:34:19 GMT
• Title: LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training
• Abstract summary: We present LAION-BVD, a large-scale open video dataset for multimodal learning.<n>It contains 1.3B platform-specific video URLs collected from CommonCrawl.<n>We download 80M videos with a total duration of 10 million hours.
• Score: 71.18006624888662
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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 training or model scale increases. Additionally, we explore video frames as an alternative source of image-text data by extracting scene-changing frames. These frames exhibit a visual distribution distinct from standard web image corpora, and models trained on this dataset achieve strong image-text retrieval performance. We release LAION-BVD to the research community. It significantly expands open access to multimodal videos at an unprecedented scale.

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