Learning the Depths of Moving People by Watching Frozen People

Learning the Depths of Moving People by Watching Frozen People

25 April 2019

William T. Freeman

Papers citing "Learning the Depths of Moving People by Watching Frozen People"

7 / 57 papers shown

Title
Weakly-Supervised 3D Human Pose Learning via Multi-view Images in the Wild Umar Iqbal Pavlo Molchanov Jan Kautz 3DH 15 117 0 17 Mar 2020
DiverseDepth: Affine-invariant Depth Prediction Using Diverse Data Wei Yin Xinlong Wang Chunhua Shen Yifan Liu Zhi Tian Songcen Xu Changming Sun Dou Renyin 3DH MDE 19 70 0 03 Feb 2020
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer René Ranftl Katrin Lasinger David Hafner Konrad Schindler V. Koltun MDE 60 1,746 0 02 Jul 2019
Pixel-Accurate Depth Evaluation in Realistic Driving Scenarios Tobias Gruber Mario Bijelic Felix Heide W. Ritter Klaus C. J. Dietmayer MDE 3DV 38 29 0 21 Jun 2019
Deep Ordinal Regression Network for Monocular Depth Estimation Huan Fu Biwei Huang Chaohui Wang Kayhan Batmanghelich Dacheng Tao MDE 200 1,708 0 06 Jun 2018
DensePose: Dense Human Pose Estimation In The Wild R. Güler Natalia Neverova Iasonas Kokkinos 3DH 184 1,386 0 01 Feb 2018
ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras Raul Mur-Artal Juan D. Tardós 204 5,375 0 20 Oct 2016