Learning Embedding of 3D models with Quadric Loss

Understand

Sharp features such as edges and corners play an important role in the perception of 3D models.

• In order to capture them better, we propose quadric loss, a point-surface loss function, which minimizes the quadric error between the reconstructed points and the input surface.
• Computation of Quadric loss is easy, efficient since the quadric matrices can be computed apriori, and is fully differentiable, making quadric loss suitable for training point and mesh based architectures.
• Through extensive experiments we show the merits and demerits of quadric loss.