| --- |
| license: cc-by-4.0 |
| task_categories: |
| - visual-question-answering |
| language: |
| - en |
| tags: |
| - VQA |
| - Benchamrk |
| - RS |
| - Bongard |
| size_categories: |
| - n<1K |
| --- |
| # BMRS: Bongard-Maximov Problems for Remote Sensing |
| * **Official Dataset for BMRS:** Bongard–Maximov Problems for Remote Sensing [Preprints.org](https://www.preprints.org/manuscript/202606.1484) |
| * **Official Code:** [GitHub](https://github.com/iitpvisionlab/BMRS). |
| ## Contents |
| This dataset includes: |
| ### BMRS/ |
| Bongard problems are stored as complete collages of images and separate images. |
| For each Bongard Problem: |
| - **right/** - all right images |
| - **left/** - all left images |
| - **pairs/** - image pairs |
| - **collage.png** - complete problem |
| - **left.png** - left side collage |
| - **right.png** - right side collage |
| ### /LLM-as-a-Judge |
| Additional data needed to run the benchmark. |
| - **answer_examples_en.json** - correct and incorrect answers examples |
| - **judge_system_prompt_en.txt** - base prompt for the judge |
| - **reference_answers_en.json** - reference correct answers |
| - **task_type_judge_prompts_en.json** - task type specific prompts for judge |
| - **tasks_en.json** - task types list for each problem |
| ## Dataset Structure |
| ``` |
| |
| BMRS/ |
| ├── BMRS/ |
| │ ├── bb_m_01/ |
| │ ├── left/ |
| │ │ ├── im0.png |
| │ │ ├── ... |
| │ │ └── im5.png |
| │ ├── pairs/ |
| │ │ ├── im0.png |
| │ │ ├── ... |
| │ │ └── im5.png |
| │ ├── right/ |
| │ │ ├── im0.png |
| │ │ ├── ... |
| │ │ └── im5.png |
| │ ├── collage.png |
| │ ├── left.png |
| │ └── right.png |
| │ ├── ... |
| │ └── bb_s_59/ |
| │ ├── left/ |
| │ │ ├── im0.png |
| │ │ ├── ... |
| │ │ └── im5.png |
| │ ├── pairs/ |
| │ │ ├── im0.png |
| │ │ ├── ... |
| │ │ └── im5.png |
| │ ├── right/ |
| │ │ ├── im0.png |
| │ │ ├── ... |
| │ │ └── im5.png |
| │ ├── collage.png |
| │ ├── left.png |
| │ └── right.png |
| ├── LLM-as-a-Judge/ |
| │ ├── answer_examples_en.json |
| │ ├── judge_system_prompt_en.txt |
| │ ├── reference_answers_en.json |
| │ ├── task_type_judge_prompts_en.json |
| │ └── tasks_en.json |
| ├── data/ |
| └── test.parquet |
| prompting_strategies.json |
| ``` |
| ## Changelog |
| ## Data Source |
| - AID: Xia, Gui-Song, et al. "AID: A benchmark data set for performance evaluation of aerial scene classification." _IEEE Transactions on Geoscience and Remote Sensing_ 55.7 (2017): 3965-3981. |
| - VisDrone: Zhu, Pengfei, et al. "Detection and tracking meet drones challenge." _IEEE transactions on pattern analysis and machine intelligence_ 44.11 (2021): 7380-7399. |
| - DOTA: Ding, Jian, et al. "Object detection in aerial images: A large-scale benchmark and challenges." _IEEE transactions on pattern analysis and machine intelligence_ 44.11 (2021): 7778-7796. |
| - MLRSNet: Qi, Xiaoman, et al. "MLRSNet: A multi-label high spatial resolution remote sensing dataset for semantic scene understanding." _ISPRS Journal of Photogrammetry and Remote Sensing_ 169 (2020): 337-350. |
| - HyperHazeOff: Nikonorov, Artem, et al. "HyperHazeOff: Hyperspectral Remote Sensing Image Dehazing Benchmark." _Journal of Imaging_ 11.12 (2025): 422. |
| - WAID: Mou, Chao, et al. "Waid: A large-scale dataset for wildlife detection with drones." _Applied Sciences_ 13.18 (2023): 10397. |
| ## Citation |
| ``` |
| @article{202606.1484, |
| doi = {10.20944/preprints202606.1484.v1}, |
| url = {https://doi.org/10.20944/preprints202606.1484.v1}, |
| year = 2026, |
| month = {June}, |
| publisher = {Preprints}, |
| author = {Nikita Firsov and Olga Terekhova and Nikita Odinets and Alexey Fedotov and Artem Muzyka and Anna Ukhanaeva and Anastasia Sarycheva and Sergei Gladilin and Dmitry Sidorchuk}, |
| title = {BMRS: Bongard–Maximov Problems for Remote Sensing}, |
| journal = {Preprints} |
| } |
| ``` |
| ## License |
| This dataset is released under license: [cc-by-4.0](https://creativecommons.org/licenses/by/4.0/) |
