The KITTI Vision Benchmark Suite

We propose a novel monocular 3D detection framework based on dense 2D-3D correspondences，which learns the object 3D geometry in a self-supervised manner and locates the object using PnP algorithm. The framework is fully uncertainty-aware, i.e., it outputs the aleatoric uncertainty of the reconstructed geometry, which is subsequently propagated through the uncertainty-aware PnP algorithm, yielding object pose with covariance.

TBD

@inproceedings{monorun,
author = {Hansheng Chen and Yuyao Huang and Wei Tian and Zhong Gao and Lu Xiong},
title = {MonoRUn: Monocular 3D Object Detection by Reconstruction and Uncertainty Propagation},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = 2021
}