Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow Estimation

Eddy Ilg, Tonmoy Saikia, Margret Keuper, Thomas Brox; The European Conference on Computer Vision (ECCV), 2018, pp. 614-630

Abstract


Occlusions play an important role in optical flow and disparity estimation, since matching costs are not available in occluded areas and occlusions indicate motion boundaries. Moreover, occlusions are relevant for motion segmentation and scene flow estimation. In this paper, we present an efficient learning-based approach to estimate occlusion areas jointly with optical flow or disparities. The estimated occlusions and motion boundaries clearly improve over the state of the art. Moreover, we present networks with state-of-the-art performance on the popular KITTI benchmark and good generic performance. Making use of the estimated occlusions, we also show imprved results on motion segmentation and scene flow estimation.

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[bibtex]
@InProceedings{Ilg_2018_ECCV,
author = {Ilg, Eddy and Saikia, Tonmoy and Keuper, Margret and Brox, Thomas},
title = {Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow Estimation},
booktitle = {The European Conference on Computer Vision (ECCV)},
month = {September},
year = {2018}
}