README.md

metadata

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 | Code

Dataset Summary

This dataset is Task 2 of 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

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.

Citation

If you find this useful in your research, please consider citing:

@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}
}