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ARID Video Action dataset
Load ARID in Python with one line of code. Stream ARID while training ML models. Visualize 3,780 video clips for surveillance and self-driving.
Visualization of the ARID dataset on the Activeloop Platform

ARID dataset

What is ARID Dataset?

Action Recognition in the Dark (ARID) is an action recognition dataset useful in a variety of situations, including night surveillance and self-driving at night. Although progress has been achieved in the action recognition task for videos in normal lighting, few studies have been conducted in the dark. ARID has over 3,780 video clips divided into 11 action categories. It is one of the first datasets focusing on human actions in dark videos.

Download ARID Dataset in Python

Instead of downloading the ARID dataset in Python, you can effortlessly load it in Python via our open-source package Hub with just one line of code.

Load ARID Dataset Training Subset in Python

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import hub
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ds = hub.load("hub://activeloop/arid-video-action-train")
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Load ARID Dataset Testing Subset in Python

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import hub
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ds = hub.load("hub://activeloop/arid-video-action-test")
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ARID Dataset Structure

ARID Data Fields

  • videos: tensor containing mp4 format video.
  • activity: tensor to identify activities in the video.

ARID Data Splits

How to use ARID Dataset with PyTorch and TensorFlow in Python

Train a model on ARID dataset with PyTorch in Python

Let's use Hub's built-in PyTorch one-line dataloader to connect the data to the compute:
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dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)
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Train a model on Arid dataset with TensorFlow in Python

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dataloader = ds.tensorflow()
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Additional Information about ARID Dataset

ARID Dataset Description

  • Repository: N/A
  • Paper: Xu, Yuecong and Yang, Jianfei and Cao, Haozhi and Mao, Kezhi and Yin, Jianxiong and See, Simon in ARID: A New Dataset for Recognizing Action in the Dark.
  • Point of Contact: N/A

ARID Dataset Curators

Xiangxin Zhu; Deva RamananXu, Yuecong and Yang, Jianfei and Cao, Haozhi and Mao, Kezhi and Yin, Jianxiong and See, Simon

ARID Dataset Licensing Information

Hub users may have access to a variety of publicly available datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets. It is your responsibility to determine whether you have permission to use the datasets under their license.
If you're a dataset owner and do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thank you for your contribution to the ML community!

ARID Dataset Citation Information

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@article{xu2020arid,
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title={ARID: A New Dataset for Recognizing Action in the Dark},
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author={Xu, Yuecong and Yang, Jianfei and Cao, Haozhi and Mao, Kezhi and Yin, Jianxiong and See, Simon},
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journal={arXiv preprint arXiv:2006.03876},
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year={2020}
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}
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ARID Dataset FAQs

What is the ARID dataset for Python?

Action Recognition in the Dark (ARID) is a popular benchmark dataset for action recognition models. The video dataset has over 3,780 video clips divided into 11 action categories. It is one of the first datasets focusing on human actions in dark videos.
How to download the ARID dataset in Python?
You can load ARID dataset fast with one line of code using the open-source package Activeloop Hub in Python. See detailed instructions on how to load ARID dataset training subset and testing subset in Python.

How can I use Arid dataset in PyTorch or TensorFlow?

You can stream Arid dataset while training a model in PyTorch or TensorFlow with one line of code using the open-source package Activeloop Hub in Python. See detailed instructions on how to train a model on AFW dataset with PyTorch in Python or train a model on arid dataset with TensorFlow in Python.