magicleap / SuperGluePretrainedNetwork

SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)
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Bug in relative pose estimation? #145

Open MarkYu98 opened 1 year ago

MarkYu98 commented 1 year ago

In utils.py L292: https://github.com/magicleap/SuperGluePretrainedNetwork/blob/ddcf11f42e7e0732a0c4607648f9448ea8d73590/models/utils.py#L292

f_mean = np.mean([K0[0, 0], K1[1, 1], K0[0, 0], K1[1, 1]])

Shouldn't it be

f_mean = np.mean([K0[0, 0], K0[1, 1], K1[0, 0], K1[1, 1]])?

Though it might not cause any noticeable difference since most cameras have similar fx and fy :)

zhangsngood commented 9 months ago

Hello! There are also some questions hereabout eatimation issues. I would like to know how the relative extrinsic parameters in ./assets/scannet_test_pairs_with_gt.txt are obtained. If I know the camera pose extrinsics of two images, how is the relative pose extrinsics T_0to1 between these two poses. Does anyone have any idea about it?