| --- |
| language: |
| - en |
| license: cc |
| size_categories: |
| - 1K<n<10K |
| task_categories: |
| - text-to-image |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: label |
| dtype: |
| class_label: |
| names: |
| '0': Aeolian_Bedforms |
| '1': Aeolian_Dunes |
| '2': Aeolian_Ripples |
| '3': Barchan_Dunes |
| '4': Boulder_Track |
| '5': Brain_Terrain |
| '6': Bright_Rays_Craters |
| '7': Central_Peak_Crater |
| '8': Chaos |
| '9': Cliff |
| '10': Concentric_Crater_Fill |
| '11': Crater_Chain |
| '12': Crater_Cluster |
| '13': Dark_Ray_Craters |
| '14': Double_Ring_Basin |
| '15': Doublet_Crater |
| '16': Dune_Field |
| '17': Dust_Devil_Tracks |
| '18': Fan_Shape_Deposit |
| '19': Fractured_Mounds |
| '20': Fresh_Crater |
| '21': Gully |
| '22': Landslide |
| '23': Lava_Flow_Front |
| '24': Lava_Tubes |
| '25': Layers |
| '26': Linear_Dunes |
| '27': Lobate_Debris_Apron |
| '28': Outflow_Channel |
| '29': Pancake_Crater |
| '30': Pedestal_Crater |
| '31': Pitted_Cone |
| '32': Pitted_Terrain |
| '33': Polar_Layered_Deposits |
| '34': Polygons |
| '35': Rampart_Crater |
| '36': Rocky_Ejecta_Crater |
| '37': Scalloped_Depression |
| '38': Slope_Streaks |
| '39': Spider |
| '40': Swiss_Cheese |
| '41': Transverse_Aeolian_Ridges |
| '42': Troughs |
| '43': Valley_Networks |
| '44': Volcano |
| '45': Wind_Streaks |
| '46': Wrinkle_Ridges |
| '47': Yardangs |
| splits: |
| - name: train |
| num_bytes: 763505091 |
| num_examples: 1185 |
| download_size: 758103040 |
| dataset_size: 763505091 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| tags: |
| - planet |
| - multimodal |
| - retrieval |
| --- |
| |
| # Landform Retrieval |
|
|
| [**Paper**](https://huggingface.co/papers/2602.13961) | [**Code**](https://github.com/ml-stat-Sustech/MarsRetrieval) |
|
|
| ## Dataset Summary |
|
|
| This dataset is Task 2 of [**MarsRetrieval**](https://github.com/ml-stat-Sustech/MarsRetrieval), a retrieval-centric benchmark for evaluating vision-language models (VLMs) on Mars geospatial discovery. Task 2 evaluates **concept-to-instance generalization** for Martian geomorphology. Given a textual geomorphic concept, the model must retrieve its corresponding visual instances from a curated Martian image gallery. The dataset comprises **1,185** carefully curated image patches collected from CTX and HiRISE imagery. The landforms follow a two-level geomorphology taxonomy: |
|
|
| - **7 major genetic classes** (e.g., Aeolian, Volcanic and Fluvial processes) |
| - **48 geomorphic subclasses** (e.g., Aeolian Dunes, Dust Devil Tracks, Yardangs) |
|
|
| ## Task Formulation |
|
|
| We formulate this task as a **text-to-image multi-positive retrieval problem**: |
|
|
| - A text query describes a geomorphic subclass. |
| - Multiple image instances in the gallery are considered valid positives. |
| - The goal is to rank all gallery images by cosine similarity in the embedding space. |
|
|
|
|
| ### Metrics |
|
|
| We report metrics suitable for long-tailed multi-positive retrieval: |
|
|
| - Macro mean Average Precision (mAP) |
| - nDCG@10 |
| - Hits@10 |
|
|
|
|
| ## How to Use |
| ```python |
| from datasets import load_dataset |
| |
| # Load the dataset |
| dataset = load_dataset("SUSTech/Mars-Landforms") |
| |
| # Access a sample image and its geomorphic label |
| print(dataset["train"][0]["image"]) |
| print(dataset["train"][0]["label"]) |
| ``` |
| For detailed instructions on the retrieval-centric protocol and official evaluation scripts, please refer to our [Official Dataset Documentation](https://github.com/ml-stat-Sustech/MarsRetrieval/blob/main/docs/DATASET.md). |
|
|
| ## Citation |
|
|
| If you find this useful in your research, please consider citing: |
|
|
| ```bibtex |
| @article{wang2026marsretrieval, |
| title={MarsRetrieval: Benchmarking Vision-Language Models for Planetary-Scale Geospatial Retrieval on Mars}, |
| author={Wang, Shuoyuan and Wang, Yiran and Wei, Hongxin}, |
| journal={arXiv preprint arXiv:2602.13961}, |
| year={2026} |
| } |
| ``` |
