Synthetic Visual Genome 2: Extracting Large-scale Spatio-Temporal Scene Graphs from Videos

We introduce Synthetic Visual Genome 2 (SVG2), a large-scale panoptic video scene graph dataset. SVG2 contains over 636K videos with 6.6M objects, 52.0M attributes, and 6.7M relations, providing an order-of-magnitude increase in scale and diversity over prior spatio-temporal scene graph datasets. To create SVG2, we design a fully automated pipeline that combines multi-scale panoptic segmentation, online-offline trajectory tracking with automatic new-object discovery, per-trajectory semantic parsing, and GPT-5-based spatio-temporal relation inference. Human verification of SVG2 annotation accuracy confirms its reliability (objects: 93.8%, attributes: 88.3%, relations: 85.4%). Building on t...

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