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images
imagewidth (px)
64
64
ord_labels
class label
10 classes
cl_labels
sequencelengths
3
3
0sulphur-butterfly
[ 8, 3, 6 ]
0sulphur-butterfly
[ 3, 9, 8 ]
0sulphur-butterfly
[ 1, 3, 3 ]
0sulphur-butterfly
[ 9, 8, 5 ]
0sulphur-butterfly
[ 3, 7, 2 ]
0sulphur-butterfly
[ 3, 8, 3 ]
0sulphur-butterfly
[ 2, 1, 1 ]
0sulphur-butterfly
[ 3, 9, 3 ]
0sulphur-butterfly
[ 8, 2, 3 ]
0sulphur-butterfly
[ 1, 8, 7 ]
0sulphur-butterfly
[ 8, 3, 6 ]
0sulphur-butterfly
[ 6, 8, 3 ]
0sulphur-butterfly
[ 2, 2, 8 ]
0sulphur-butterfly
[ 3, 5, 6 ]
0sulphur-butterfly
[ 8, 3, 1 ]
0sulphur-butterfly
[ 7, 3, 7 ]
0sulphur-butterfly
[ 3, 4, 2 ]
0sulphur-butterfly
[ 8, 3, 3 ]
0sulphur-butterfly
[ 3, 1, 1 ]
0sulphur-butterfly
[ 8, 8, 1 ]
0sulphur-butterfly
[ 3, 3, 9 ]
0sulphur-butterfly
[ 5, 3, 1 ]
0sulphur-butterfly
[ 3, 8, 8 ]
0sulphur-butterfly
[ 8, 8, 7 ]
0sulphur-butterfly
[ 4, 2, 3 ]
0sulphur-butterfly
[ 8, 9, 3 ]
0sulphur-butterfly
[ 8, 8, 2 ]
0sulphur-butterfly
[ 1, 3, 8 ]
0sulphur-butterfly
[ 3, 3, 5 ]
0sulphur-butterfly
[ 2, 7, 8 ]
0sulphur-butterfly
[ 2, 8, 8 ]
0sulphur-butterfly
[ 1, 8, 3 ]
0sulphur-butterfly
[ 7, 8, 8 ]
0sulphur-butterfly
[ 3, 6, 8 ]
0sulphur-butterfly
[ 6, 7, 6 ]
0sulphur-butterfly
[ 1, 3, 8 ]
0sulphur-butterfly
[ 8, 9, 1 ]
0sulphur-butterfly
[ 1, 3, 3 ]
0sulphur-butterfly
[ 3, 8, 5 ]
0sulphur-butterfly
[ 6, 8, 7 ]
0sulphur-butterfly
[ 8, 6, 7 ]
0sulphur-butterfly
[ 1, 3, 8 ]
0sulphur-butterfly
[ 8, 8, 8 ]
0sulphur-butterfly
[ 9, 8, 5 ]
0sulphur-butterfly
[ 8, 8, 3 ]
0sulphur-butterfly
[ 3, 9, 6 ]
0sulphur-butterfly
[ 3, 8, 2 ]
0sulphur-butterfly
[ 7, 1, 1 ]
0sulphur-butterfly
[ 8, 2, 2 ]
0sulphur-butterfly
[ 8, 3, 1 ]
0sulphur-butterfly
[ 3, 1, 4 ]
0sulphur-butterfly
[ 8, 7, 8 ]
0sulphur-butterfly
[ 1, 3, 3 ]
0sulphur-butterfly
[ 7, 8, 9 ]
0sulphur-butterfly
[ 9, 8, 8 ]
0sulphur-butterfly
[ 6, 7, 3 ]
0sulphur-butterfly
[ 2, 1, 3 ]
0sulphur-butterfly
[ 3, 3, 8 ]
0sulphur-butterfly
[ 6, 9, 5 ]
0sulphur-butterfly
[ 9, 6, 3 ]
0sulphur-butterfly
[ 9, 3, 3 ]
0sulphur-butterfly
[ 8, 8, 3 ]
0sulphur-butterfly
[ 3, 8, 3 ]
0sulphur-butterfly
[ 3, 3, 8 ]
0sulphur-butterfly
[ 3, 8, 3 ]
0sulphur-butterfly
[ 1, 9, 1 ]
0sulphur-butterfly
[ 7, 8, 4 ]
0sulphur-butterfly
[ 3, 7, 8 ]
0sulphur-butterfly
[ 3, 8, 7 ]
0sulphur-butterfly
[ 1, 8, 3 ]
0sulphur-butterfly
[ 8, 8, 8 ]
0sulphur-butterfly
[ 2, 3, 9 ]
0sulphur-butterfly
[ 7, 8, 5 ]
0sulphur-butterfly
[ 3, 1, 2 ]
0sulphur-butterfly
[ 3, 8, 3 ]
0sulphur-butterfly
[ 2, 7, 8 ]
0sulphur-butterfly
[ 3, 8, 3 ]
0sulphur-butterfly
[ 8, 2, 2 ]
0sulphur-butterfly
[ 1, 3, 2 ]
0sulphur-butterfly
[ 9, 1, 8 ]
0sulphur-butterfly
[ 1, 8, 8 ]
0sulphur-butterfly
[ 3, 1, 3 ]
0sulphur-butterfly
[ 2, 8, 8 ]
0sulphur-butterfly
[ 3, 3, 8 ]
0sulphur-butterfly
[ 8, 8, 1 ]
0sulphur-butterfly
[ 3, 8, 8 ]
0sulphur-butterfly
[ 8, 3, 3 ]
0sulphur-butterfly
[ 1, 8, 3 ]
0sulphur-butterfly
[ 8, 2, 1 ]
0sulphur-butterfly
[ 3, 3, 7 ]
0sulphur-butterfly
[ 8, 1, 9 ]
0sulphur-butterfly
[ 6, 8, 1 ]
0sulphur-butterfly
[ 2, 3, 2 ]
0sulphur-butterfly
[ 3, 9, 8 ]
0sulphur-butterfly
[ 8, 3, 7 ]
0sulphur-butterfly
[ 3, 3, 6 ]
0sulphur-butterfly
[ 3, 3, 3 ]
0sulphur-butterfly
[ 1, 9, 9 ]
0sulphur-butterfly
[ 1, 8, 1 ]
0sulphur-butterfly
[ 5, 3, 9 ]
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Dataset Card for ACLMicroImageNet10

This Complementary labeled MicroImageNet10 dataset contains 3 human-annotated complementary labels for all 5000 images in the training split of TinyImageNet200.

For more details, please visit our github or paper.

Dataset Structure

Data Instances

A sample from the training set is provided below:

{
    'images': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=64x64 at 0x77CB6DF65F30>, 
    'ord_labels': 0, 
    'cl_labels': [8, 3, 6]
}

Data Fields

  • images: A PIL.Image.Image object containing the 64x64 image.

  • ord_labels: The ordinary labels of the images, and they are labeled from 0 to 9 as follows:

    0: sulphur-butterfly 1: backpack 2: cardigan 3: kimono 4: magnetic-compass 5: oboe 6: scandal 7: torch 8: pizza 9: alp

  • cl_labels: Three complementary labels for each image.

Citing

If you find this dataset useful, please cite the following:

@InProceedings{aclimage2025,
  author="Mai, Tan-Ha and Ye, Nai-Xuan and Kuan, Yu-Wei and Lu, Po-Yi and Lin, Hsuan-Tien",
  title="The Unexplored Potential of Vision-Language Models for Generating Large-Scale Complementary-Label Learning Data",
  booktitle="Pacific-Asia Conference on Knowledge Discovery and Data Mining",
  year="2025",
  pages="90--102"
}
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