A supervised model does not learn the world; it learns the labels a team of annotators assigned to pixels. If those labels ...

Datasets are a primary driver of progress in computer vision, and many computer vision applications require datasets that include human faces. These datasets often have labels denoting racial identity ...

Multi-label image classification extends the traditional single-label paradigm by assigning multiple simultaneous labels to each image, reflecting the complexity of real-world scenes. This task poses ...

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...