Text-guided 3D shape generation remains challenging due to the absence of large paired
text-shape data, the substantial semantic gap between these two modalities, and the
structural complexity of 3D shapes. This paper presents a new framework called Image as
Stepping Stone (ISS) for the task by introducing 2D image as a stepping stone to connect the
two modalities and to eliminate the need for paired text-shape data. Our key contribution is a
two-stage feature-space-alignment approach that maps CLIP features to shapes by …

In this paper, we present a new text-guided 3D shape generation approach DreamStone
that uses images as a stepping stone to bridge the gap between text and shape modalities
for generating 3D shapes without requiring paired text and 3D data. The core of our
approach is a two-stage feature-space alignment strategy that leverages a pre-trained single-
view reconstruction (SVR) model to map CLIP features to shapes: to begin with, map the
CLIP image feature to the detail-rich 3D shape space of the SVR model, then map the CLIP …