The invention discloses a face detection method based on a cascaded connection convolutional neural network. The method is realized by two steps of training and testing. Firstly, image preprocessing is carried out, an image to be tested is subjected to scale transformation, and the test image is input into a first-hierarchy network. Then, in a first hierarchy, a full convolution network is adoptedto generate face candidate boxes. On a second hierarchy, a non-maximum value inhabitation method is adopted to further filter the obtained face candidate boxes. Finally, in a third-hierarchy network,the face box is screened and further regressed, and the face is filtered for the last time. According to the method, the compact neural network is adopted, image data features are enhanced through acascade connection network method, image noise is lowered, and a good effect is achieved on the aspects of accuracy and speed.