In this report, we present our champion solutions to five tracks at Ego4Dchallenge. We leverage our developed InternVideo, a video foundation model, forfive Ego4D tasks, including Moment Queries, Natural Language Queries, FutureHand Prediction, State Change Object Detection, and Short-term ObjectInteraction Anticipation. InternVideo-Ego4D is an effective paradigm to adaptthe strong foundation model to the downstream ego-centric video understandingtasks with simple head designs. In these five tasks, the performance ofInternVideo-Ego4D comprehensively surpasses the baseline methods and thechampions of CVPR2022, demonstrating the powerful representation ability ofInternVideo as a video foundation model. Our code will be released athttps://github.com/OpenGVLab/ego4d-eccv2022-solutions