  Capturing the 3D geometry of transparent objects is a challenging task,
ill-suited for general-purpose scanning and reconstruction techniques, since
these cannot handle specular light transport phenomena. Existing
state-of-the-art methods, designed specifically for this task, either involve a
complex setup to reconstruct complete refractive ray paths, or leverage a
data-driven approach based on synthetic training data. In either case, the
reconstructed 3D models suffer from over-smoothing and loss of fine detail.
This paper introduces a novel, high precision, 3D acquisition and
reconstruction method for solid transparent objects. Using a static background
with a coded pattern, we establish a mapping between the camera view rays and
locations on the background. Differentiable tracing of refractive ray paths is
then used to directly optimize a 3D mesh approximation of the object, while
simultaneously ensuring silhouette consistency and smoothness. Extensive
experiments and comparisons demonstrate the superior accuracy of our method.
