HRNet explained: Human Pose Estimation, Sematic Segmentation and Object Detection

HRNet is a state-of-the-art algorithm in the field of semantic segmentation, facial landmark detection, and human pose estimation. It has shown superior results in semantic segmentation on datasets like PASCAL Context, LIP, Cityscapes, AFLW, COFW, and 300W. But first, let's understand what the fields mean and what kind of algorithm hides behind HRNet. Semantic Segmentation is used to categorize structures of an image into certain classes. This is done by labeling each pixel with a certain class [3].