A video is nothing but a series of images. Video brings a new dimension to the image along the temporal direction. The spatial features of the images and temporal features of the video can be put together, providing a better outcome than just the image. The extra dimension also results in a lot of space and hence increases the complexity of training and inference. The computational demands are extremely high for processing a video. Video also changes the architecture of deep learning models as we have to consider the temporal features. 

Video classification is the task of labeling a video with a category. A category can be on the frame level or for the whole video. There could be actions or tasks performed in the video. Hence, a video classification may label the objects present in the video or label the actions happening in the video. In the next section, we will see the available datasets for video classification tasks.