青岛大学学报（自然科学版）2024，Vol.37Issue(1)：39-44,51,7.DOI:10.3969/j.issn.1006-1037.2024.01.07
基于局部区域强化的单目深度估计算法
Monocular Depth Estimation Methcd Based on Local Regional Reinforcement
摘要
Abstract
A monocular depth estimation method based on local regional reinforcement was proposed to ad-dress the issues of object boundary distortion and loss of local detail information caused by complex texture and geometry structare in depth estimation scene.First,the depth estimation model based on the convolu-tional neural network was used to obtain the low-resolution image.Then,the saliency object detection model was introduced to obtain the high-resolution saliency map which supervised the generation of depth map.Finally,the salient map and depth map were fused to improve the overall depth estimation accuracy of the image.Experimental results on public datasets show that the proposed method can significantly im-prove the precision of monocular depth estimation.关键词
单目深度估计/局部区域强化/卷积神经网络/深度学习Key words
monocular depth estimation/local regional reinforcement/convolutional neural network deep learning分类
信息技术与安全科学引用本文复制引用
王乐刚,陈程立诏..基于局部区域强化的单目深度估计算法[J].青岛大学学报（自然科学版）,2024,37(1):39-44,51,7.基金项目
国家自然科学基金(批准号:61772294)资助 （批准号:61772294）
山东省高等学校青年创新科技支持计划项目(批准号:2021KJ062)资助. （批准号:2021KJ062）
