PDC-Net+: Enhanced Probabilistic Dense Correspondence Network

Understand

Establishing robust and accurate correspondences between a pair of images is a long-standing computer vision problem with numerous applications.

• While classically dominated by sparse methods, emerging dense approaches offer a compelling alternative paradigm that avoids the keypoint detection step.
• However, dense flow estimation is often inaccurate in the case of large displacements, occlusions, or homogeneous regions.
• In order to apply dense methods to real-world applications, such as pose estimation, image manipulation, or 3D reconstruction, it is therefore crucial to estimate the confidence of the predicted matches.