How To Use UCF101, The Largest Dataset Of Human Actions

In this article, we have presented UCF101 which is one of the most testing dataset for activity acknowledgement contrasted with the current ones. It incorporates 101 activity classes and over 13k clips

UCF-101 dataset has 101 actions and 13320 clips of human actions, collected from youtube were first introduced in 2012 by researchers: Khurram Soomro, Amir Roshan Zamir and Mubarak Shah of Center for Research in Computer Vision, Orlando, FL 32816, USA. The clips in the action class are divided into 25 groups. Each group contains 4-7 clips. Clips in each group share some common features like background or actor.

UCF Sports, UCF11, UCF50 and UCF101 are the datasets arranged by UCF in sequential order, each one incorporates its forerunner. UCF-101 is the largest among them with 101 classes. This dataset gives the biggest variety as far as activities and with the presence of huge varieties in camera movement, object appearance and posture, object scale, perspective, jumbled foundation, light conditions.

Here, we will discuss the dataset and see how to load the dataset using TensorFlow and PyTorch. Further, we will implement the UCF-101 dataset in TensorFlow.

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