The invention provides a remote sensing image rotation target detection method based on multistage fusion and angular point offset. The method is used for solving the technical problems that in the prior art, the detection accuracy of targets with different scales is low, and the running speed of the detection process is low. The method comprises the following implementation steps of: 1, acquiring a minimum enclosing rectangle of a rotary marking box of each target; 2, generating a training set; 3, constructing a deep full convolutional neural network; 4, training the deep full convolutional neural network; 5, detecting a rotating target in the image; 6, post-processing the box of the rotating target; and 7, drawing the final rotation detection boxes of all targets at corresponding positions in the image to obtain a detection result graph. According to the invention, targets with different scales in the image can be better distinguished, false detection is reduced, and the precision of the target box after image target detection is improved.