The aim of this paper is to provide a com- prehensive overview of the MICCAI 2020 AutoImplant Chal- lenge. The approaches and publications submitted and accepted within the challenge will be summarized and re- ported, highlighting common algorithmic trends and algo- rithmic diversity. Furthermore, the evaluation results will be presented, compared and discussed in regard to the challenge aim: seeking for low cost, fast and fully auto- mated solutions for cranial implant design. Based on feed- back from collaborating neurosurgeons, this paper con- cludes by stating open issues and post-challenge require- ments for intra-operative use. The codes can be found at https://github.com/Jianningli/tmi.