In the rapidly evolving field of computer vision, the task of accuratelyestimating the poses of multiple individuals from various viewpoints presents aformidable challenge, especially if the estimations should be reliable as well.This work presents an extensive evaluation of the generalization capabilitiesof multi-view multi-person pose estimators to unseen datasets and presents anew algorithm with strong performance in this task. It also studies theimprovements by additionally using depth information. Since the new approachcan not only generalize well to unseen datasets, but also to differentkeypoints, the first multi-view multi-person whole-body estimator is presented.To support further research on those topics, all of the work is publiclyaccessible.