ARID Video Action dataset

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Visualization of the ARID dataset in the Deep Lake UI

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 Deep Lake open-source with just one line of code.

Load ARID Dataset Training Subset in Python

				
					import deeplake
ds = deeplake.load("hub://activeloop/arid-video-action-train")

Load ARID Dataset Testing Subset in Python

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

ARID Dataset Structure

ARID Data Fields

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

ARID Data Splits

The arid dataset training set is composed of 4416.
The arid dataset testing set is composed of 1791.

How to use ARID Dataset with PyTorch and TensorFlow in Python

Train a model on the ARID dataset with PyTorch in Python

Let’s use Deep Lake built-in PyTorch one-line dataloader to connect the data to the compute:

				
					dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)

Train a model on the ARID dataset with TensorFlow in Python

				
					dataloader = ds.tensorflow()

Additional Information about ARID Dataset

ARID Dataset Description

Homepage: https://xuyu0010.github.io/arid.html
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

Deep Lake 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

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

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.

What is the ARID dataset for Python?

You can load the ARID dataset fast with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to load the ARID dataset training subset and testing subset in Python.

How can I use ARID dataset in PyTorch or TensorFlow?

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