Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation

We investigate two crucial and closely-related aspects of CNNs for optical flow estimation: models and training. First, we design a compact but effective CNN model, called PWC-Net, according to simple and well-established principles: pyramidal processing, warping, and cost volume processing. PWC-Net...

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Vydané v:	IEEE transactions on pattern analysis and machine intelligence Ročník 42; číslo 6; s. 1408 - 1423
Hlavní autori:	Sun, Deqing, Yang, Xiaodong, Liu, Ming-Yu, Kautz, Jan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.06.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptive optics and convolutional neural network (CNN) cost volume Databases, Factual Empirical analysis Estimation Humans Image Processing, Computer-Assisted - methods Network architecture Neural Networks, Computer Optical flow Optical flow (image analysis) Optical imaging Optical signal processing Protocol (computers) Protocols pyramid Software Training warping
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
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