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Efficient Stereo Depth Estimation for Pseudo LiDAR: A Self-Supervised
  Approach Based on Multi-Input ResNet Encoder

Efficient Stereo Depth Estimation for Pseudo LiDAR: A Self-Supervised Approach Based on Multi-Input ResNet Encoder

Italian National Conference on Sensors (INS), 2022
17 May 2022
Sabir Hossain
Xianke Lin
    3DPCMDE
ArXiv (abs)PDFHTMLGithub

Papers citing "Efficient Stereo Depth Estimation for Pseudo LiDAR: A Self-Supervised Approach Based on Multi-Input ResNet Encoder"

2 / 2 papers shown
Universal Bovine Identification via Depth Data and Deep Metric Learning
Universal Bovine Identification via Depth Data and Deep Metric Learning
Asheesh Sharma
Lucy Randewich
William Andrew
S. Hannuna
Neill D. F. Campbell
Siobhan Mullan
A. W. Dowsey
Melvyn Smith
Mark Hansen
T. Burghardt
292
4
0
29 Mar 2024
VoloGAN: Adversarial Domain Adaptation for Synthetic Depth Data
VoloGAN: Adversarial Domain Adaptation for Synthetic Depth DataSocial Science Research Network (SSRN), 2022
Sascha Kirch
Rafael Pagés
Sergio Arnaldo
S. Martín
GAN
236
2
0
19 Jul 2022
1
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