Digging Into Self-Supervised Monocular Depth Estimation: Difference between revisions
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Affiliations: UCL, Caltech, Niantic | Affiliations: UCL, Caltech, Niantic | ||
* [https://arxiv.org/abs/1806.01260 Arxiv mirror] | * [https://arxiv.org/abs/1806.01260 Arxiv mirror] [https://openaccess.thecvf.com/content_ICCV_2019/html/Godard_Digging_Into_Self-Supervised_Monocular_Depth_Estimation_ICCV_2019_paper.html CVF Mirror] | ||
* [https://github.com/nianticlabs/monodepth2 Github] | * [https://github.com/nianticlabs/monodepth2 Github] | ||
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===Per-Pixel Minimum Reprojection Loss=== | ===Per-Pixel Minimum Reprojection Loss=== | ||
Basically you have two images in a sequence: frame1, frame2, frame3. | |||
Each gives you a loss: | |||
<pre> | |||
loss1 = abs(frame2 - warp(frame1)) | |||
loss2 = abs(frame2 - warp(frame3)) | |||
# Take the minimum over all pixels | |||
loss = mean(min(loss1, loss2)) | |||
</pre> | |||
===Auto-Masking Stationary Pixels=== | ===Auto-Masking Stationary Pixels=== | ||
===Multi-scale Estimation=== | ===Multi-scale Estimation=== | ||