✨Synthetic Visual Genome 2: Extracting Large-scale Spatio-Temporal Scene Graphs from Videos
📝 Summary:
A large video scene graph dataset, SVG2, and a new model, TRaSER, are introduced. TRaSER generates spatio-temporal scene graphs, significantly improving relation, object, and attribute prediction, and boosting video question answering accuracy.
🔹 Publication Date: Published on Feb 26
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.23543
• PDF: https://arxiv.org/pdf/2602.23543
• Project Page: https://uwgzq.github.io/papers/SVG2/
🔹 Models citing this paper:
• https://huggingface.co/UWGZQ/TRASER
✨ Datasets citing this paper:
• https://huggingface.co/datasets/UWGZQ/Synthetic_Visual_Genome2
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For more data science resources:
✓ https://t.iss.one/DataScienceT
#VideoSceneGraphs #SpatioTemporal #ComputerVision #VideoQA #DeepLearning
📝 Summary:
A large video scene graph dataset, SVG2, and a new model, TRaSER, are introduced. TRaSER generates spatio-temporal scene graphs, significantly improving relation, object, and attribute prediction, and boosting video question answering accuracy.
🔹 Publication Date: Published on Feb 26
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.23543
• PDF: https://arxiv.org/pdf/2602.23543
• Project Page: https://uwgzq.github.io/papers/SVG2/
🔹 Models citing this paper:
• https://huggingface.co/UWGZQ/TRASER
✨ Datasets citing this paper:
• https://huggingface.co/datasets/UWGZQ/Synthetic_Visual_Genome2
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#VideoSceneGraphs #SpatioTemporal #ComputerVision #VideoQA #DeepLearning
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