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--- |
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license: apache-2.0 |
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--- |
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# DyFo: Test Code and Datasets |
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This repository contains the test code and evaluation data for **DyFo: A Training-Free Dynamic Focus Visual Search for Enhancing LMMs in Fine-Grained Visual Understanding** (CVPR 2025 Highlight). |
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For the full implementation, please refer to the main codebase at: |
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👉 https://github.com/PKU-ICST-MIPL/DyFo_CVPR2025 |
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## 📦 How to Use |
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1. Download and unzip this dataset into the root directory of the main repository. |
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2. This package includes evaluation code and processed data for testing the DyFo method. |
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## 📚 Included Datasets |
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The following benchmark datasets are included for evaluation: |
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- **POPE-COCO/A-OKVQA/GQA** |
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Original source: https://github.com/RUCAIBox/POPE |
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- **Vstar** |
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Original source: https://github.com/penghao-wu/vstar |
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These datasets are pre-processed and ready to use with our test code. |
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## 📄 License |
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This dataset and code are licensed under the Apache 2.0 License. |
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## 📑 Citation |
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If you use DyFo in your work, please cite: |
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```bibtex |
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@misc{li2025dyfotrainingfreedynamicfocus, |
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title={DyFo: A Training-Free Dynamic Focus Visual Search for Enhancing LMMs in Fine-Grained Visual Understanding}, |
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author={Geng Li and Jinglin Xu and Yunzhen Zhao and Yuxin Peng}, |
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year={2025}, |
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eprint={2504.14920}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV}, |
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url={https://arxiv.org/abs/2504.14920} |
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} |
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