The invention provides a deep learning-based non-supervision video segmentation method. The method comprises the following steps of: establishing a coding/decoding deep neural network, wherein the coding/decoding deep neural network comprises a static image segmentation flow network, an inter-frame information segmentation flow network and a fusion network, the static image segmentation flow network is used for carrying out foreground/background segmentation on the current video frame, and the inter-frame information segmentation flow network is used for carrying foreground/background segmentation of a movement object on optical flow field information between the current video frame and the next video frame; and obtaining a video segmentation result after fusing segmented images output bythe static image segmentation flow network and the inter-frame information segmentation flow network through the fusion network. The static image segmentation flow network is used for high-quality inter-frame segmentation, the inter-frame information segmentation flow network is used for high-quality optical flow field information segmentation, and two paths of output are fused through the final fusion operation so as to obtain the enhanced segmentation result, so that a relatively good segmentation result can be obtained according to effective two-path output and fusion operation.