PCTDepth: Exploiting Parallel CNNs and Transformer via Dual Attention for Monocular Depth Estimation

Monocular depth estimation (MDE) has made great progress with the development of convolutional neural networks (CNNs). However, these approaches suffer from essential shortsightedness due to the utilization of insufficient feature-based reasoning. To this end, we propose an effective parallel CNNs a...

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Veröffentlicht in:	Neural processing letters 2024-02, Vol.56 (2), p.73, Article 73
Hauptverfasser:	Xia, Chenxing, Duan, Xiuzhen, Gao, Xiuju, Ge, Bin, Li, Kuan-Ching, Fang, Xianjin, Zhang, Yan, Yang, Ke
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial Intelligence Artificial neural networks Complex Systems Computational Intelligence Computer Science Deep learning Energy consumption Model accuracy Modules Neural networks Sensors Success Transformers
Online-Zugang:	Volltext
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