ATRDataset / README.md
ckotait's picture
Upload dataset
7826e22
|
raw
history blame
No virus
2.19 kB
metadata
dataset_info:
  features:
    - name: pixel_values
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': label
            '1': pixel_values
  splits:
    - name: train
      num_bytes: 125816829.116
      num_examples: 33412
    - name: test
      num_bytes: 7589050
      num_examples: 2000
  download_size: 797334593
  dataset_size: 133405879.116
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*

Dataset Card for Dataset Name

The Active Template Regression (ATR) dataset comprises 18 semantic category labels, including face, sunglasses, hat, scarf, hair, upper clothes, left arm, right arm, belt, pants, left leg, right leg, skirt, left shoe, right shoe, bag, dress, and background. A total of 17,700 images were incorporated into the ATR dataset. 16,700 images were designated for training, and 1,000 for testing.

  • Curated by: Xiaodan Liang, Si Liu, Xiaohui Shen, Jianchao Yang, Luoqi Liu, Jian Dong, Liang Lin, Shuicheng Yan
  • Shared by: Xiaodan Liang, Si Liu, Xiaohui Shen, Jianchao Yang, Luoqi Liu, Jian Dong, Liang Lin, Shuicheng Yan
  • License: MIT

Dataset Sources

Human Parsing Labels

  • 0: background
  • 1: hat
  • 2: hair
  • 3: sunglasses
  • 4: upperclothes
  • 5: skirt
  • 6: pants
  • 7: dress
  • 8: belt
  • 9: leftshoe
  • 10: rightshoe
  • 11: face
  • 12: leftleg
  • 13: rightleg
  • 14: leftarm
  • 15: rightarm
  • 16: bag
  • 17: scarf

Uses

Semantic segmentation, and more specifically, human body parsing.

Dataset Card Authors

Christian Kotait

BibTeX:

@article{liang2015deep, title={Deep human parsing with active template regression}, author={Liang, Xiaodan and Liu, Si and Shen, Xiaohui and Yang, Jianchao and Liu, Luoqi and Dong, Jian and Lin, Liang and Yan, Shuicheng}, journal={IEEE transactions on pattern analysis and machine intelligence}, volume={37}, number={12}, pages={2402--2414}, year={2015}, publisher={IEEE} }