  Sketches are the most abstract 2D representations of real-world objects.
Although a sketch usually has geometrical distortion and lacks visual cues,
humans can effortlessly envision a 3D object from it. This suggests that
sketches encode the information necessary for reconstructing 3D shapes. Despite
great progress achieved in 3D reconstruction from distortion-free line
drawings, such as CAD and edge maps, little effort has been made to reconstruct
3D shapes from free-hand sketches. We study this task and aim to enhance the
power of sketches in 3D-related applications such as interactive design and
VR/AR games.
  Unlike previous works, which mostly study distortion-free line drawings, our
3D shape reconstruction is based on free-hand sketches. A major challenge for
free-hand sketch 3D reconstruction comes from the insufficient training data
and free-hand sketch diversity, e.g. individualized sketching styles. We thus
propose data generation and standardization mechanisms. Instead of
distortion-free line drawings, synthesized sketches are adopted as input
training data. Additionally, we propose a sketch standardization module to
handle different sketch distortions and styles. Extensive experiments
demonstrate the effectiveness of our model and its strong generalizability to
various free-hand sketches. Our code is publicly available at
https://github.com/samaonline/3D-Shape-Reconstruction-from-Free-Hand-Sketches.
