🥇 UniGenBench Leaderboard (English)

📚 UniGenBench is a unified benchmark for T2I generation that integrates diverse prompt themes with a comprehensive suite of fine-grained evaluation criteria.

🔧 You can use the official GitHub repo to evaluate your model on UniGenBench.

😊 We release all generated images from the T2I models evaluated in our UniGenBench on UniGenBench-Eval-Images. Feel free to use any evaluation model that is convenient and suitable for you to assess and compare the performance of your models.

📝 To add your own model to the leaderboard, please send an Email to Yibin Wang, then we will help with the evaluation and updating the leaderboard.

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📙 Citation

If you use UniGenBench in your research, please cite our work: