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A Contrastive Compositional Benchmark for Text-to-Image Synthesis: A Study with Unified Text-to-Image Fidelity Metrics

Xiangru Zhu1, Penglei Sun2, Chengyu Wang3, Jingping Liu4, Zhixu Li1, Yanghua Xiao1, Jun Huang3

1Fudan University, 2The Hong Kong University of Science and Technology (Guangzhou), 3Alibaba Group, 4East China University of Science and Technology

Paper

Failed cases on Stable Diffusion XL 1.0

Evaluation results from SDXL and IF

Updates

  • ✅ Winoground-T2I Dataset and Templates
  • ⬜ Images Generated (7 Benchmarks) and T2I Fidelity Metric Results (9 Metrics)
  • ⬜ Code for Data Collection
  • ⬜ Code for Evaluating the Reliability of Metrics from 4 Perspectives
  • ⬜ Results of Human Evaluation and Code for the Annotation Interface
  • ⬜ Code for the improved version of LLMScore with self-verification

Dataset

Winoground-T2I Dataset: data/dataset/

Templates: data/template/

Acknowledgments

We makes use of several T2I fidelity metrics to evaluate T2I synthesis models.