To infer the 3D shape of an object, the visual system often relies on 2D retinal input. For ideal specular surfaces, the retinal image is a deformation of the surrounding environment. Since many configurations of shape and environment can potentially generate the same retinal image, 3D specular shape estimation is ambiguous. A relative motion between object, observer and environment produces dynamic information on the retina, called specular flow. From a computational point of view, this specular flow may diminish perceptual ambiguities. For this research, two novel, smooth shapes were rendered with two different environment maps (a forest and a city) and under two motion conditions (static and dynamic). In the dynamic condition, the surface and the observer were kept relatively static, but the surrounding environment map was rotated at sinusoidal speed around the vertical axis, generating ‘flowing’ reflections on the surface. Eight observers performed the gauge figure task (attitude probe) with these stimuli. The analysis of variance indicated that both inter-observer correlations and correlations with the 3D input model were higher for the static presentation than for the dynamic one. Results imply that specular flow, despite offering a computational advantage, is not beneficially used by the human visual system.