Binocular digital fringe projection has been widely used in three-dimensional (3D) shape measurement. However, for objects with considerable variations in surface reflectance, the information on digital fringes may be lost due to overexposure, resulting in a decrease in measurement accuracy. Therefore, this paper proposes an adaptive binocular digital fringe projection method to address this issue. First, grayscale images with different intensities are projected onto the object's surface to create a mask image. Furthermore, multiple sets of saturated point pixel clusters are generated, and the surface reflectance of the object within these clusters is calculated. Besides, the optimal projection light intensity value for each pixel in the clusters of saturated pixel points is determined. Second, the generated adaptive digital fringe sequence is projected onto the object's surface using the mapping relationship between the camera and projector pixel points. Finally, the phase is solved using the multifrequency heterodyne method, and the 3D object shape is reconstructed through phase matching performed by the left and right cameras. The experimental results show that the proposed method achieves a reduction of 99.57% and 96.57% in phase root mean square and average relative errors, respectively, compared with the existing binocular methods. Additionally, more accurate phase extraction and matching of the saturated exposure area are realized, and the relative error of height in the fitting model is reduced by 72.12%, thereby enhancing the measurement accuracy of the 3D shape of the strongly reflective object surfaces.