Image Recognition: Datasets and Algorithms

This lecture delves into a 2019 paper proposing a novel approach to image recognition by separating images into shape and appearance components, discussing the datasets used, such as celebrity images, cat head photos, and bird images, and highlighting the challenges and biases in dataset creation. It also explores the impact of large-scale datasets like ImageNet on deep learning models, the importance of ground truths, and the evolution of datasets over time.