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OpenVid-1M: A High-Quality Dataset for Text-to-Video Generation
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OpenVid-1M addresses two critical challenges in text-to-video (T2V) generation: the scarcity of high-quality datasets and the underutilization of text data. This innovative dataset, comprising more than a million text-video pairs, features 433K high-definition videos. A novel model, the Multi-modal Video Diffusion Transformer (MVDiT), improves video generation by more effectively integrating text and visual data. Experimental results demonstrate enhancements over prior methods.
Scores | Value | Explanation |
---|---|---|
Objectivity | 7 | Balanced reporting with comprehensive analysis. |
Social Impact | 4 | Influences AI and video generation communities. |
Credibility | 6 | Solid evidence from authoritative sources. |
Potential | 6 | Could lead to significant advancements in T2V generation. |
Practicality | 5 | Directly applicable to real-world problems. |
Entertainment Value | 3 | Some appeal to tech and AI enthusiasts. |