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pro vyhledávání: '"Bailer, Christian"'
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 evaluated with top accuracy on different data sets. In our analysis of the
Externí odkaz:
http://arxiv.org/abs/1805.03517
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 taken so far to extract local features efficiently for a whole image. In t
Externí odkaz:
http://arxiv.org/abs/1805.03096
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 large-baseline novel view synthesis problem is far from being "solved".
Externí odkaz:
http://arxiv.org/abs/1804.09690
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 scene flow estimation in an automotive or commercial vehicle context t
Externí odkaz:
http://arxiv.org/abs/1801.04720
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 interpolation of sparse matches. To this end, we find sparse matches acro
Externí odkaz:
http://arxiv.org/abs/1710.10096
Modern large displacement optical flow algorithms usually use an initialization by either sparse descriptor matching techniques or dense approximate nearest neighbor fields. While the latter have the advantage of being dense, they have the major disa
Externí odkaz:
http://arxiv.org/abs/1703.02563
Learning based approaches have not yet achieved their full potential in optical flow estimation, where their performance still trails heuristic approaches. In this paper, we present a CNN based patch matching approach for optical flow estimation. An
Externí odkaz:
http://arxiv.org/abs/1607.08064
Modern large displacement optical flow algorithms usually use an initialization by either sparse descriptor matching techniques or dense approximate nearest neighbor fields. While the latter have the advantage of being dense, they have the major disa
Externí odkaz:
http://arxiv.org/abs/1508.05151
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