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Found 6 papers, 3 papers with code
Edge-aware Consistent Stereo Video Depth Estimation
As a benefit of using stereo inputs, a left-right consistency loss is introduced to improve the performance.
Leveraging Multi-view Data for Improved Detection Performance: An Industrial Use Case
Printed circuit boards (PCBs) are essential components of electronic devices, and ensuring their quality is crucial in their production.
TriStereoNet: A Trinocular Framework for Multi-baseline Disparity Estimation
Stereo vision is an effective technique for depth estimation with broad applicability in autonomous urban and highway driving.
Ranked #1 on
Stereo Depth Estimation
on KITTI2015
(D1-all All metric)
Separable Convolutions for Optimizing 3D Stereo Networks
In this work first, we show that these 3D convolutions in stereo networks consume up to 94% of overall network operations and act as a major bottleneck.
MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching
Depending on the dimension of cost volume, we design a 2D and a 3D model with encoder-decoders built from 2D and 3D convolutions, respectively.
Ranked #1 on
Stereo Depth Estimation
on sceneflow
Object detection and Autoencoder-based 6D pose estimation for highly cluttered Bin Picking
Bin picking is a core problem in industrial environments and robotics, with its main module as 6D pose estimation.
