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Publication Authors

Prof. Dr. Didier Stricker

Dr. Alain Pagani

Dr. Gerd Reis

Eric Thil

Keonna Cunningham

Dr. Oliver Wasenmüller

Dr. Gabriele Bleser

Dr. Jason Raphael Rambach

Dr. Bertram Taetz

Sk Aziz Ali

Rashed Al Koutayni
Yuriy Anisimov

Jilliam Maria Diaz Barros

Ramy Battrawy
Hammad Butt

Mahdi Chamseddine
Steve Dias da Cruz

Fangwen Shu

Torben Fetzer

Michael Fürst

Christiano Couto Gava

Tewodros Amberbir Habtegebrial
Khurram Hashmi

Jigyasa Singh Katrolia

Andreas Kölsch
Onorina Kovalenko

Stephan Krauß
Paul Lesur

Muhammad Jameel Nawaz Malik
Michael Lorenz

Mina Ameli

Nareg Minaskan Karabid

Pramod Murthy

Mathias Musahl

Peter Neigel

Manthan Pancholi
María Alejandra Sánchez Marín
Dr. Kripasindhu Sarkar

Alexander Schäfer

René Schuster

Mohamed Selim

Dennis Stumpf

Yongzhi Su

Xiaoying Tan
Yaxu Xie
Murad Almadani

Ahmet Firintepe

Dr. Vladislav Golyanik

Dr. Aditya Tewari

André Luiz Brandão
SceneFlowFields++: Multi-frame Matching, Visibility Prediction, and Robust Interpolation for Scene Flow Estimation
SceneFlowFields++: Multi-frame Matching, Visibility Prediction, and Robust Interpolation for Scene Flow Estimation
René Schuster, Oliver Wasenmüller, Christian Unger, Georg Kuschk, Didier Stricker
International Journal of Computer Vision (IJCV) tba Springer 2019 .
- Abstract:
- State-of-the-art scene flow algorithms pursue the conflicting targets of accuracy, run time, and robustness. With the successful concept of pixel-wise matching and sparse-to-dense interpolation, we shift the operating point in this field of conflicts towards universality and speed. Avoiding strong assumptions on the domain or the problem yields a more robust algorithm. This algorithm is fast because we avoid explicit regularization during matching, which allows an efficient computation. Using image information from multiple time steps and explicit visibility prediction based on previous results, we achieve competitive performances on different data sets. Our contributions and results are evaluated in comparative experiments. Overall, we present an accurate scene flow algorithm that is faster and more generic than any individual benchmark leader.