The Chinese research team has collaboratively developed the innovative multi-view dataset "FreeMan," aimed at addressing the limitations of existing 3D human pose estimation datasets. This dataset comprises 11 million frames from 8 smartphones, covering both indoor and outdoor environments with diverse lighting conditions, providing a rich resource for the diversity of real-world scenarios. Researchers have generated accurate 3D annotations through an automated labeling process, which can be used for various tasks such as single 2D to 3D conversion, multi-view 3D estimation, and neural rendering. The open-source release of the FreeMan dataset will promote the development of large-scale pre-training datasets and also provides a new benchmark for outdoor 3D human pose estimation. This innovation is expected to drive advancements in human modeling, computer vision, and human-computer interaction, bridging the gap between controlled laboratory conditions and real-world scenarios.