26 citations · 35 across the 5 of their papers we have counts for
8 papers
FlowFields++: Accurate Optical Flow Correspondences Meet Robust Interpolation
René Schuster, Christian Bailer, Oliver Wasenmüller +1
Optical Flow algorithms are of high importance for many applications. Recently, the Flow Field algorithm and its modifications have shown remarkable results, as they have been eval…
Fast Feature Extraction with CNNs with Pooling Layers
Christian Bailer, Tewodros Habtegebrial, Kiran varanasi +1
In recent years, many publications showed that convolutional neural network based features can have a superior performance to engineered features. However, not much effort was take…
Fast View Synthesis with Deep Stereo Vision
Tewodros Habtegebrial, Kiran Varanasi, Christian Bailer +1
Novel view synthesis is an important problem in computer vision and graphics. Over the years a large number of solutions have been put forward to solve the problem. However, the la…
Combining Stereo Disparity and Optical Flow for Basic Scene Flow
René Schuster, Christian Bailer, Oliver Wasenmüller +1
Scene flow is a description of real world motion in 3D that contains more information than optical flow. Because of its complexity there exists no applicable variant for real-time…
SceneFlowFields: Dense Interpolation of Sparse Scene Flow Correspondences
René Schuster, Oliver Wasenmüller, Georg Kuschk +2
While most scene flow methods use either variational optimization or a strong rigid motion assumption, we show for the first time that scene flow can also be estimated by dense int…
Flow Fields: Dense Correspondence Fields for Highly Accurate Large Displacement Optical Flow Estimation
Christian Bailer, Bertram Taetz, Didier Stricker
Modern large displacement optical flow algorithms usually use an initialization by either sparse descriptor matching techniques or dense approximate nearest neighbor fields. While…