Monocular Depth Estimation: A Survey 来自 Semantic Scholar 喜欢 0 阅读量: 464 作者: A Bhoi 摘要: Monocular depth estimation is often described as an ill- posed and inherently ambiguous problem. Estimating depth from 2D images is a crucial step in scene reconstruction, 3D object recognition, ...
人体姿态估计综述(Monocular Human Pose Estimation: A Survey of Deep Learning-based Methods),程序员大本营,技术文章内容聚合第一站。
This survey is organized in the following way. Section sect. 2 introduces some widely used datasets and evaluation indicators in monocular depth estimation. Section sect. 3 reviews some representative depth estimation methods based on deep learning according to different training modes. We also conclude...
A. Bhoi. “Monocular depth estimation: A survey.” arXiv preprint arXiv: 1901.09402, 2019.. Google Scholar [2] Z. He, L. Q Jin, and C. Ye. An RGB-D camera based visual positioning system for assistive navigation by a robotic navigation aid. IEEE/CAA J. Autom. Sin. , 2021 ...
In this review paper, we survey numerous existing literature on monocular depth estimation along with various datasets, as well as several supervised, unsupervised and semi-supervised algorithms. Furthermore, we figured out the drawbacks of the existing traditional methods and discussed contemporary ...
We present MoNA Bench, a benchmark for Monocular depth estimation in Navigation of the Autonomous unmanned Aircraft system (MoNA), emphasizing its obstacle avoidance and safe target tracking capabilities. We highlight key attributes—estimation efficiency, depth map accuracy, and scale consistency—for ...
Self-supervised monocular depth estimation has received much attention recently in computer vision. Most of the existing works in literature aggregate multi-scale features for depth prediction via either straightforward concatenation or element-wise addi
estimation based on monocular images or videos remains a very challenging task due to a variety of difficulties such as depth ambiguities, occlusion, background clutters, and lack of training data. In this survey, we summarize recent advances in monocular 3D human pose estimation. We provide a ...
The fast estimation of the IMU bias and the MAP of the scale accelerates the speed of the scale convergence during the initialization, and also provides a more accurate initial data for the back-end optimization to reduce the cumulative error. In the depth estimation, the depth filtering scheme...
GCNDepth 0.4246.7573.075 GCNDepth: Self-supervised Monocular Depth Estimation based on Graph Convolutional Network 2021 5 AnyNet [88] 0.232 A Survey on Deep Learning Techniques for Stereo-based Depth Estimation 2020 6 HighResNet [32] 0.474