The invention discloses an MCS (Mesoscale Convection System) identification and tracking method based on image anchor-frame-free detection, which comprises the following steps of: step 1, preprocessing infrared brightness temperature data of an original stationary satellite, carrying out mesoscale convection system marking on an infrared cloud picture obtained after processing, and then randomly dividing a training set, a verification set and a test set; step 2, constructing an instance segmentation network based on no anchor frame, the network being used for extracting image features, detecting a mesoscale convection system and segmenting specific instances; step 3, performing training set image enhancement, using a transfer learning supervised training instance to segment the convolutional neural network, and automatically learning network parameters; step 4, performing mesoscale convection system detection and segmentation on the geostationary satellite infrared nephograms at adjacent moments by using the trained model; and step 5, realizing the tracking of the mesoscale convection system according to a related target matching principle.