118 citations · 258 across the 21 of their papers we have counts for
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eess.IV2019★ 29 cited
On the Benefit of Adversarial Training for Monocular Depth Estimation
Rick Groenendijk, Sezer Karaoglu, Theo Gevers +1
In this paper we address the benefit of adding adversarial training to the task of monocular depth estimation. A model can be trained in a self-supervised setting on stereo pairs o…
cs.CV2019★ 2 cited
3D Neighborhood Convolution: Learning Depth-Aware Features for RGB-D and RGB Semantic Segmentation
Yunlu Chen, Thomas Mensink, Efstratios Gavves
A key challenge for RGB-D segmentation is how to effectively incorporate 3D geometric information from the depth channel into 2D appearance features. We propose to model the effect…