We put the sampled images and corresponding annotation files into datasets folder. The full data will be released immediately after the paper is accepted.

Datasets

You can find the descriptions of our datasets at here

Codebase

The structure of this codebase is as follows:

- datasets
    - README.md: instructions to download our datasets.

- src: codes for repeating experiments.
    - supervised: codes for traditional object detectors (section V-B in our paper).
    - open_vocabulary: codes for benchmarking open-vocabulary object detectors (section V-C in our paper).
        - cora
        - detic
        - gdino
        - vild

    - post_process: codes for improving the open-vocabulary object detectors (section V-D).

Reference

BibTeX Style Citation

@article{liu2025fine,
  title={Fine-Grained Open-Vocabulary Object Detection with Fined-Grained Prompts: Task, Dataset and Benchmark},
  author={Liu, Ying and Hua, Yijing and Chai, Haojiang and Wang, Yanbo and Ye, TengQi},
  journal={arXiv preprint arXiv:2503.14862},
  year={2025}
}