Context. The complex shape of asteroids and comets is a critical parameter in many scientific and operational studies. From the global irregular shape down to the local surface details, these topographies reflect the formation and evolutionary processes that remould the celestial body. Furthermore, these processes control how the surface will continue to evolve: from mass wasting on high slopes to spin-up due to anisotropic re-emission of thermal radiation. In addition, for space missions, the irregular coarse shape and complex landscape are a hazard to navigation, which must be accounted for in the planning phase. Aims. In this paper, we propose a novel method to synthesize physically correct 3D shape models of small celestial bodies, such as asteroids, to support the testing of a wide range of parameters in scientific and operational studies. Methods. We modeled virtual asteroid shapes using non-uniform sphere packings to represent the coarse shape, define an implicit surface, and then synthesize high-resolution topography with user-defined, locally controlled spot noise models. This effectively replaces the random noise model (e.g., Perlin noise) used in traditional approaches and allows us to construct a morphology based on actual physical shapes of the most common features observed on asteroids and comets. As an example of such a feature, we propose several kernel functions to add virtual craters to the coarse shape of the asteroid, of which the spatial distribution is controlled by typical crater production functions (e.g., a power law). Results. We demonstrate how this technique can be used to generate a variety of asteroid shapes and topographies using different cratering parameters and distributions. We apply our technique to artificially increase the resolution of existing models of the Didymos-Dimorphos system, the target of the Double Asteroid Redirection Test, and Hera missions. We show that our approach generates models that are suitable for typical analysis relying on detailed asteroid shapes, as well as operational scenarios for space missions. The meshes created with our algorithm can be directly used with existing visualization software and operations or science pipelines to generate data suitable for mission planning and to validate data analysis techniques.