We propose a generative model based method for recovering both the shape and the reflectance of the surface(s) of a scene from multiple images, assuming that illumination conditions and cameras calibration are known in advance. Based on a variational framework and via gradient descents, the algorithm minimizes simultaneously and consistently a global cost functional with respect to both shape and reflectance. Contrary to previous work which considers and specializes in a specific scenario, our method applies indiscriminately with a number of classical scenarios; in particular it works for classical stereovision, multiview photometric stereo and multiview shape from shading. Moreover, unlike most previous methods dealing with only Lambertian surfaces, the proposed method considers general dichromatic surfaces. We verify the method using synthetic and real data sets containing specular reflection.