README.md

---
license: apache-2.0
task_categories:
  - image-to-text
language:
  - en
pretty_name: CAPEval
size_categories:
  - n<1K
tags:
  - captioning
  - multimodal
  - evaluation
  - checklist
  - coverage
  - precision
papers:
  - https://arxiv.org/abs/2608.02589
citation: |
  @article{liu2026capeval,
    title={CAPEval: A Decoupled Caption Evaluation across Understanding and Generation},
    author={Liu, Zhipeng and Wang, Haochen and Zhang, Zhaoxiang},
    journal={arXiv preprint arXiv:2608.02589},
    year={2026}
  }
---

# CAPEval

**CAPEval** (Coverage And Precision Evaluation) is a checklist-based caption evaluation benchmark.
It decouples caption quality into **Coverage (C)** and **Precision (P)** (0–100), and studies how each profile transfers to VLM understanding and T2I generation.

- Code / docs: [liuzhipenggg/CAPEval](https://github.com/liuzhipenggg/CAPEval)
- Project page: [liuzhipenggg.github.io/CAPEval](https://liuzhipenggg.github.io/CAPEval/)
- Paper: [arXiv:2608.02589](https://arxiv.org/abs/2608.02589)
- Leaderboard: [leaderboard](https://liuzhipenggg.github.io/CAPEval/leaderboard/)

## Dataset contents

| Path | Description |
|------|-------------|
| `image/` | 300 high-resolution images (up to 8K) |
| `gt_caption.jsonl` | Human-written ground-truth captions |
| `checklist.jsonl` | Human-verified atomic checklist items (**14,965** total) |
| `meta/` | Category / label metadata tables |

Join key across files: image basename / `img_path` (e.g. `SO001.jpg`).

**4** super-categories: Scene & Object · People & Activity · Text & Interface · Design & Knowledge.

## Metrics (in code)

CAPEval judges each caption against checklist items (`yes` / `no` / `not_mentioned`):

| Metric | Definition |
|--------|------------|
| **C** | `100 × (yes + no) / total` — coverage |
| **P** | `100 × yes / (yes + no)` — precision |

## Quick start

```bash
hf download LiuzhipengUCAS/CAPEval --repo-type dataset --local-dir ./capeval_data
```

Then point CAPEval env vars at the downloaded paths (see the GitHub README / `examples/cluster_run.md`).

## Citation

```bibtex
@article{liu2026capeval,
  title={CAPEval: A Decoupled Caption Evaluation across Understanding and Generation},
  author={Liu, Zhipeng and Wang, Haochen and Zhang, Zhaoxiang},
  journal={arXiv preprint arXiv:2608.02589},
  year={2026}
}
```

## License

Apache License 2.0 — see the code repository `LICENSE`.