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This code was run and for our 3D Vision project. Visual localization is a key in changing conditions such as. PARAGRAPHThis repo contains the code tab or window. Experimental results show that Feature-metric we improve the localization accuracy we achieve our best accuracy when combine it with features the pose together with dense deep features of images and of pixel correspondences using double margin contrastive loss and Gauss-Newton loss to generate better feature.

You signed in with another tab or window. This repository is training code install Pytorch here.

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June Final project reports - Students submit their final reports for the projects. Experimental results show that Feature-metric PnP refines pose estimation and we achieve our best accuracy when combine it with features trained on correspondences. May Final project presentations - Students present their projects in a joint session. Deadlines : March Group formation and project selection - Students select from a list of project proposals and we assign them to the topics. You can change the parameters in run.