Lightweight Self-Supervised Monocular Depth Estimation Through CNN and Transformer Integration

Self-supervised monocular depth estimation is a promising research area due to its ability to train models without relying on expensive and difficult-to-obtain ground truth depth labels. In this domain, models often employ Convolutional Neural Networks (CNNs) and Transformers for feature extraction....

תיאור מלא

מידע ביבליוגרפי

Principais autores:	Zhe Wang, Yongjia Zou, Jin Lv, Yang Cao, Hongfei Yu
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	IEEE 2024-01-01
סדרה:	IEEE Access
נושאים:	Machine vision monocular depth estimation lightweight self-supervised learning
גישה מקוונת:	https://ieeexplore.ieee.org/document/10749800/
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!