This work is licensed under a Creative Commons Attribution .
We release MarsData-V2, a rock segmentation dataset of real Martian scenes for the training of deep networks, extended from our previously published MarsData [1]. The raw unlabeled RGB images of MarsData-V2 are from here, which were collected by a Mastcam camera of the Curiosity rover on Mars between August 2012 and November 2018. After sorting out images with an opportune shooting distance, labeling Mars rocks with fine-grained boundaries, and performing data augmentation referring to [2], we obtained 8390 labeled images with a resolution of 512 × 512, and divided them into 5040 images for training, 1680 for validation and 1670 for testing.
We show 8 samples, including 4 samples in MarsData and 4 new ones in MarsData-V2, where the Martian rocks with varying shapes, sizes, textures and colors are labeled with fine-grained annotations.
4 samples in MarsData:
4 new samples in MarsData-V2:
Limited by the file size, we temporarily release 100 samples in the train, validation and test set of MarsData-V2 on github, respectively. The whole data can be found by the following way:
[1]: IEEE DataPort;
[2]: If you do not acess to IEEE DataPort, please contact us by email(alexcapshow@cust.edu.cn or meibaoyao@jlu.edu.cn) and sign the data license aggrement to get the dataset .
If you use MarsDataV2 for your research, please cite all the following papers and data：
@article{liu2023rockformer,
title={RockFormer: A U-Shaped Transformer Network for Martian Rock Segmentation},
author={Liu, Haiqiang and Yao, Meibao and Xiao, Xueming and Xiong, Yonggang},
journal={IEEE Transactions on Geoscience and Remote Sensing},
volume={61},
pages={1--16},
year={2023},
publisher={IEEE}
}
@article{xiao2021kernel,
title={A Kernel-Based Multi-Featured Rock Modeling and Detection Framework for a Mars Rover},
author={Xiao, Xueming and Yao, Meibao and Liu, Haiqiang and Wang, Jiake and Zhang, Lei and Fu, Yuegang},
journal={IEEE Transactions on Neural Networks and Learning Systems},
year={2021},
doi={10.1109/TNNLS.2021.3131206},
publisher={IEEE}
}
@data{34a5-jq14-22,
doi = {10.21227/34a5-jq14},
url = {https://dx.doi.org/10.21227/34a5-jq14},
author = {Xiao, Xueming and Yao, Meibao and Liu, Haiqiang},
publisher = {IEEE Dataport},
title = {MarsData-V2, a rock segmentation dataset of real Martian scenes},
year = {2022}
}
[1] Xiao X, Yao M, Liu H, et al. A Kernel-Based Multi-Featured Rock Modeling and Detection Framework for a Mars Rover[J]. IEEE Transactions on Neural Networks and Learning Systems, 2021.
[2] Furlán F, Rubio E, Sossa H, et al. Rock detection in a Mars-like environment using a CNN[C]//Mexican Conference on Pattern Recognition. Springer, Cham, 2019: 149-158.
