Aeriform in-action is a multiview dataset for recognizing human actions in aerial videos. The proposed dataset consists of 32 high resolution videos containing 13 action classes with 55,477 frames (without augmentation) and 400,000 annotations captured at 30fps and a resolution of 3840 x 2160 pixels. The dataset addresses several concerns like camera motion, illumination changes, diversity in actions, dynamic transitions of actions etc. The action classes can be categorized as atomic actions, human- human interactions and human-object interactions. The 13 actions are carrying, drinking, handshaking, hugging, kicking, lying, punching, reading, running, sitting, standing, walking and waving. This dataset will provide a baseline for recognizing human actions in aerial videos and will encourage the embedding researchers to progress the field.