3D whole‐heart coronary MR angiography (CMRA) has shown significant potential for the diagnosis of coronary artery disease. Undersampled motion corrected reconstruction approaches have enabled free-breathing isotropic 3D CMRA in ~5-10min scan time. However, spatial resolution is still limited compared to coronary CT angiography and scan time remains relatively long. In this work, we propose a deep-learning based super-resolution (SR) framework, combined with non-rigid respiratory motion compensation (SR-CMRA), to shorten the acquisition time to <1min. A 16-fold increase in spatial resolution is achieved by reconstructing a high-resolution CMRA (1.2mm3) from a low-resolution acquisition (1.2x4.8x4.8mm3, 50s scan).