5 papers with code • 1 benchmarks • 2 datasets
However, in this paper we argue that it is not the quality of the data but its representation that accounts for the majority of the difference.
In this paper, we propose a novel system named Disp R-CNN for 3D object detection from stereo images.
Ranked #14 on Vehicle Pose Estimation on KITTI Cars Hard
In this paper, we study the problem of 3D object detection from stereo images, in which the key challenge is how to effectively utilize stereo information.
Existing approaches to depth or disparity estimation output a distribution over a set of pre-defined discrete values.
Ranked #1 on Stereo Depth Estimation on KITTI2015 (three pixel error metric)