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This report describes the approach behind our winning solution to the 2022Epic-Kitchens Action Recognition Challenge. Our approach builds upon our recentwork, Multiview Transformer for Video Recognition (MTV), and adapts it tomultimodal inputs. Our final submission consists of an ensemble of MultimodalMTV (M&M) models varying backbone sizes and input modalities. Our approachachieved 52.8% Top-1 accuracy on the test set in action classes, which is 4.1%higher than last year's winning entry.

M&M Mix: A Multimodal Multiview Transformer Ensemble