To solve the problem that Explicit Shape Regression (ESR) has low precision in face alignment, an improved explicit shape regression for face alignment algorithm was proposed. Firstly, in order to get a more accurate initial shape, three-point face shape was used as an initial shape mapping standard to replace face rectangle. Then, pixel block feature was used against illumination variations instead of pixel feature, which improved the algorithm robustness. Finally, instead of average method, the accuracy of algorithm was further improved by multiple hypothesis fusion strategy which merged multiple estimations. Compared with explicit shape regression algorithm, the simulation experimental results show that the accuracy is improved by 7.96%, 5.36% and 1.94% respectively by using the proposed algorithm on LFPW, HELEN and 300-W face datasets.