Learning Dense Wide Baseline Stereo Matching for People

Learning Dense Wide Baseline Stereo Matching for People

2 October 2019

Papers citing "Learning Dense Wide Baseline Stereo Matching for People"

10 / 10 papers shown

Title
PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization Shunsuke Saito Zeng Huang Ryota Natsume Shigeo Morishima Angjoo Kanazawa Hao Li 3DH 147 1,258 0 13 May 2019
StereoDRNet: Dilated Residual Stereo Net Rohan Chabra Julian Straub Chris Sweeney Richard Newcombe Henry Fuchs MDE 3DPC 3DV 58 103 0 03 Apr 2019
Model Adaptation with Synthetic and Real Data for Semantic Dense Foggy Scene Understanding Daniel Gehrig Dengxin Dai Simon Hecker Luc Van Gool 75 238 0 03 Aug 2018
What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? N. Mayer Eddy Ilg Philipp Fischer C. Hazirbas Daniel Cremers Alexey Dosovitskiy Thomas Brox OOD 74 213 0 19 Jan 2018
Augmentor: An Image Augmentation Library for Machine Learning Marcus D. Bloice Christof Stocker Andreas Holzinger 44 265 0 11 Aug 2017
End-to-End Learning of Geometry and Context for Deep Stereo Regression Alex Kendall H. Martirosyan Saumitro Dasgupta Peter Henry Ryan Kennedy Abraham Bachrach Adam Bry 3DV 3DPC MDE 83 1,335 0 13 Mar 2017
Fully-Convolutional Siamese Networks for Object Tracking Luca Bertinetto Jack Valmadre João F. Henriques Andrea Vedaldi Philip Torr VOT 77 3,879 0 30 Jun 2016
Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches Jure Zbontar Yann LeCun 3DV 137 1,388 0 20 Oct 2015
Learning to Compare Image Patches via Convolutional Neural Networks Sergey Zagoruyko N. Komodakis SSL 84 1,436 0 14 Apr 2015
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network David Eigen Christian Puhrsch Rob Fergus MDE 3DPC 3DV 236 4,059 0 09 Jun 2014