The neural network has been introduced into the reconstruction of the complex three-dimensional (3D) object based on structured light projection. In the network method, the neural network with powerful function of approximation is used to get the continuous approximate function of the discrete fringe pattern. The measured object can be reconstructed by dealing with the approximate function and drawing phase distribution of the object. As a result, the network method based on structured light projection need only one deformed fringe pattern to reconstruct the tested object. Compared with the Fourier transform profilometry (FTP), the neural network method without filtering process does not lose high frequency of the measured object. So it has large space bandwidth product and high sensitivity can given out the detail precisely. Therefore, this method performs better than FTP in the three-dimensional shape measurement of complex objects. Moreover, compared with FTP, the network method can demodulate more useful phase from the fringe pattern with shadow. Computer simulations and experiment validate the feasibility of this method.