Cardiac image segmentation is the problem of learning the anatomical semantics of each voxel in a three-dimensional heart image. In clinical practice, radiologists are delegated to draw contours manually, encompassing the structures of interest. The process is lengthy, monotonous, and prone to subjective errors. Starting from the 1970s, researchers have thoroughly investigated the possibility of automating this task. Automated CMR segmentation can help clinicians interpreting the medical conditions, speeding up diagnoses, increasing monitoring reliability, facilitating surgical planning, and enabling vast population studies. Overall, it would make a strong contribution to the battle against cardiovascular diseases (CVDs), estimated to cost 31\% of all global deaths.