The reconstruction of real world objects becomes even more important in the view of creating highly realistic scenes for Virtual Reality applications. In this paper, we present a fully automated algorithmic pipeline for high-quality 3D reconstruction of real world objects. The proposed method refines an initial 3D model by exploiting the results of additional pairwise stereo depth estimation. An automatic camera selection approach provides different point clouds, which are fused into a common coherent and highly detailed 3D model. The quality of the reconstruction results is discussed in comparison to several state-of-the-art tools, also in the context of automation and performance.