Normal Assisted Stereo Depth Estimation

Understand

Accurate stereo depth estimation plays a critical role in various 3D tasks in both indoor and outdoor environments.

• Recently, learning-based multi-view stereo methods have demonstrated competitive performance with a limited number of views.
• However, in challenging scenarios, especially when building cross-view correspondences is hard, these methods still cannot produce satisfying results.
• In this paper, we study how to leverage a normal estimation model and the predicted normal maps to improve the depth quality.