GA-Net: Guided Aggregation Net for End-to-end Stereo Matching

CVPR 2019 Feihu ZhangVictor PrisacariuRuigang YangPhilip H. S. Torr

In the stereo matching task, matching cost aggregation is crucial in both traditional methods and deep neural network models in order to accurately estimate disparities. We propose two novel neural net layers, aimed at capturing local and the whole-image cost dependencies respectively... (read more)

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