Stereo-LiDAR Fusion
7 papers with code • 1 benchmarks • 0 datasets
Depth estimation using stereo cameras and a LiDAR sensor.
Benchmarks
These leaderboards are used to track progress in Stereo-LiDAR Fusion
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Most implemented papers
Pyramid Stereo Matching Network
JiaRenChang/PSMNet
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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
We propose a novel deep learning architecture for regressing disparity from a rectified pair of stereo images.
Learning Guided Convolutional Network for Depth Completion
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
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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
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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
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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
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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.
