MirrorFlow: Exploiting Symmetries in Joint Optical Flow and Occlusion Estimation

Understand

Optical flow estimation is one of the most studied problems in computer vision, yet recent benchmark datasets continue to reveal problem areas of today's approaches.

• Occlusions have remained one of the key challenges.
• In this paper, we propose a symmetric optical flow method to address the well-known chicken-and-egg relation between optical flow and occlusions.
• In contrast to many state-of-the-art methods that consider occlusions as outliers, possibly filtered out during post-processing, we highlight the importance of joint occlusion reasoning in the optimization and show how to utilize occlusion as an important cue for estimating optical flow.