Deep Ordinal Regression Network for Monocular Depth Estimation

CVPR 2018 Huan FuMingming GongChaohui WangKayhan BatmanghelichDacheng Tao

Monocular depth estimation, which plays a crucial role in understanding 3D scene geometry, is an ill-posed problem. Recent methods have gained significant improvement by exploring image-level information and hierarchical features from deep convolutional neural networks (DCNNs)... (read more)

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Evaluation results from the paper

Task Dataset Model Metric name Metric value Global rank Compare
Monocular Depth Estimation KITTI Eigen split DORN absolute relative error 0.072 # 2
Monocular Depth Estimation NYU-Depth V2 DORN RMSE 0.509 # 6