Exploring the UCF101 Dataset: A Large-Scale, YouTube-Based Action Recognition Dataset

The UCF101 Action Recognition dataset is a collection of realistic action videos with 101 action categories, curated from YouTube. It was the largest video action recognition dataset available at its release in 2012 and covers various computer vision use cases such as video, images, location, point-cloud, action-recognition, classification, detection, segmentation, and relationships. The dataset is characterized by a large diversity of actions and variations in camera motion, object appearance and pose, scale, viewpoint, background, and illumination conditions. It has been used for human action recognition tasks with real-world applications like surveillance, healthcare, human-computer interaction, content-based video retrieval, and video summarization. The dataset is available as a part of the FiftyOne Dataset Zoo, which can be accessed using simple commands in the FiftyOne toolset.