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      "content": "## Introduction\nThe Stanford 40 Action Dataset contains images of humans performing 40 actions. In each image, we provide a bounding box of the person who is performing the action indicated by the filename of the image. There are 9532 images in total with 180-300 images per action class.\nYou can find more information at <a href=\"http://vision.stanford.edu/Datasets/40actions.html\">here</a>.\n\n- Please note that the original dataset is not partitioned, but we randomly split in training and test datasets for this challenge. Thus, you should not use the original dataset in this challenge.\n\n## Citations\nPlease cite this paper if you want to use this dataset in your research:\n\n- B. Yao, X. Jiang, A. Khosla, A.L. Lin, L.J. Guibas, and L. Fei-Fei. Human Action Recognition by Learning Bases of Action Attributes and Parts. <i>Internation Conference on Computer Vision (ICCV)</i>, Barcelona, Spain. November 6-13, 2011.  \n",
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      "content": "# Kyung Hee University AI7005-00 Deep Learning Lecture Project Challenge\n\n- The goal of this challenge is to achieve high performance in a given dataset using techniques learned in the lecture.\n- You can use any neural networks and find your own model architecture to find out how to achieve optimal performance.\n- To prevent using a lot of GPU resources, you should use a network that can train by using the resources provided by Google Colab.\n- The baseline is the ResNet-18 result trained on Google Colab from TA and this code will be provided for all.\n",
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      "name": "Evaluation",
      "content": "## Submission Format\n\nSubmission files should contain two columns: `Id` and `Category`. `Id` is the index of test images and 'Category' means the class of the test image.\n\nThe file should contain a header and have the following format:\n```\nId,Category\n0,15\n1,21\n2,1\n```",
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    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n- Train with only Google Colab!\n- Do not use any external datasets and pre-trained models!",
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