Stereo-LiDAR Fusion

7 papers with code • 1 benchmarks • 0 datasets

Depth estimation using stereo cameras and a LiDAR sensor.

Most implemented papers

Pyramid Stereo Matching Network

JiaRenChang/PSMNet CVPR 2018

The spatial pyramid pooling module takes advantage of the capacity of global context information by aggregating context in different scales and locations to form a cost volume.

End-to-End Learning of Geometry and Context for Deep Stereo Regression

zyf12389/GC-Net ICCV 2017

We propose a novel deep learning architecture for regressing disparity from a rectified pair of stereo images.

Learning Guided Convolutional Network for Depth Completion

kakaxi314/GuideNet 3 Aug 2019

It is thus necessary to complete the sparse LiDAR data, where a synchronized guidance RGB image is often used to facilitate this completion.

3D LiDAR and Stereo Fusion using Stereo Matching Network with Conditional Cost Volume Normalization

zswang666/Stereo-LiDAR-CCVNorm 5 Apr 2019

The complementary characteristics of active and passive depth sensing techniques motivate the fusion of the Li-DAR sensor and stereo camera for improved depth perception.

Scene Completeness-Aware Lidar Depth Completion for Driving Scenario

choyingw/SCADC-DepthCompletion 15 Mar 2020

Recent sparse depth completion for lidars only focuses on the lower scenes and produces irregular estimations on the upper because existing datasets, such as KITTI, do not provide groundtruth for upper areas.

Non-Local Spatial Propagation Network for Depth Completion

zzangjinsun/NLSPN_ECCV20 ECCV 2020

In this paper, we propose a robust and efficient end-to-end non-local spatial propagation network for depth completion.

Fusing Event-based and RGB camera for Robust Object Detection in Adverse Conditions

abhishek1411/event-rgb-fusion ICRA 2022

The ability to detect objects, under image corruptions and different weather conditions is vital for deep learning models especially when applied to real-world applications such as autonomous driving.