Monocular 3D Object Detection and Box Fitting Trained End-to-End Using Intersection-over-Union Loss

no code implementations • 19 Jun 2019 • Eskil Jörgensen, Christopher Zach, Fredrik Kahl

We show how modeling heteroscedastic uncertainty improves performance upon our baseline, and furthermore, how back-propagation can be done through the optimizer in order to train the pipeline end-to-end for additional accuracy.

Autonomous Driving Monocular 3D Object Detection +2