Shuffle in 3D: A Lightweight Architecture for Stereo Matching

The deep learning-based stereo matching approaches commonly construct 3D cost volume with a Siamese network, and the 3D encoder-decoder architectures regularize 3D cost volume to generate disparity as output. Yet, the 3D encoder-decoder architectures produce tremendous parameters that causing huge t...

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Vydané v:	2021 IEEE 10th Global Conference on Consumer Electronics (GCCE) s. 675 - 677
Hlavní autori:	Xiao, Jianqiang, Yamane, Satoshi
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 12.10.2021
Predmet:	3D ShuffleNet Computational efficiency Computer architecture Conferences Consumer electronics Costs lightweight 3D encoder-decoder Stereo Matching Three-dimensional displays Training
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