ADCV: Unsupervised depth completion employing adaptive depth-based cost volume-Reference-Cited by-同舟云学术

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ADCV: Unsupervised depth completion employing adaptive depth-based cost volume

Published:2024-12 Issue: Volume:155 Page:104750
ISSN:1051-2004
Container-title:Digital Signal Processing
language:en
Short-container-title:Digital Signal Processing

Author:

Li Tao^ORCID,Wu Dandan,Zhou Minghui,Liao Qing,Peng Yonghong

Publisher

Elsevier BV

Reference64 articles.

1. 3d object detection for autonomous driving: methods, models, sensors, data, and challenges;Ghasemieh;Transp. Eng.,2022

2. Depth-map-based augmented reality holographic stereogram: method and verification;Liu;Optik,2023

3. Reinforcement learning-driven dynamic obstacle avoidance for mobile robot trajectory tracking;Xiao;Knowl.-Based Syst.,2024

4. Sparsity invariant cnns;Uhrig,2017

5. Cu-net: lidar depth-only completion with coupled u-net;Wang;IEEE Robot. Autom. Lett.,2022

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