Compared to the good performance that can be achieved by many 2D visual attention models, predicting salient regions of a 3D scene is still challenging. An efficient way to achieve this can be to exploit existing models designed for 2D content. However, the visual conflicts caused by binocular disparity and changes of viewing behavior in 3D viewing need to be dealt with. To cope with these, the present paper proposes a simple framework for extending 2D attention models for 3D images, as well as evaluates center-bias in 3D-viewing condition. To validate the results, a database is created, which contains eye-movements of 35 subjects recorded during free viewing of eighteen 3D images and their corresponding 2D version. Fixation density maps indicate a weaker center-bias in the viewing of 3D images. Moreover, objective metric results demonstrate the efficiency of the proposed model and a large added value of center-bias when it is taken into account in computational modeling od 3D visual attention.