LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training
Summary
LAION-BVD is a large-scale open video dataset containing 10 million hours of video data for multimodal pre-training, with synthetic captions and competitive benchmark performance.
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Paper page - LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training
Source: https://huggingface.co/papers/2608.24845 Authors:
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Abstract
LAION-BVD is a large-scale open video dataset enabling multimodal pre-training across video, audio, and image modalities with synthetic captions and strong benchmark performance.
We presentLAION-BVD, a large-scale open video dataset formultimodal learning, which contains 1.3B platform-specific video URLs collected fromCommonCrawl. 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. Usingcontent-aware scene detection, we extract clips for which we synthetically generate video and audio captions. Models trained on these data achieve competitive performance on standardvideo-textandaudio-textbenchmarks, 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 strongimage-text retrievalperformance. We releaseLAION-BVDto the research community. It significantly expands open access to multimodal videos at an unprecedented scale.
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