Monocular depth estimation based on deep learning: An overview
Depth information is important for autonomous systems to perceive environments and
estimate their own state. Traditional depth estimation methods, like structure from motion …
estimate their own state. Traditional depth estimation methods, like structure from motion …
Structure from motion photogrammetry in forestry: A review
Abstract Purpose of Review The adoption of Structure from Motion photogrammetry (SfM) is
transforming the acquisition of three-dimensional (3D) remote sensing (RS) data in forestry …
transforming the acquisition of three-dimensional (3D) remote sensing (RS) data in forestry …
On the opportunities and risks of foundation models
AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
Depth-regularized optimization for 3d gaussian splatting in few-shot images
This paper presents a method to optimize Gaussian splatting with a limited number of
images while avoiding overfitting. Representing a 3D scene by combining numerous …
images while avoiding overfitting. Representing a 3D scene by combining numerous …
An overview of ongoing point cloud compression standardization activities: Video-based (V-PCC) and geometry-based (G-PCC)
D Graziosi, O Nakagami, S Kuma… - … Transactions on Signal …, 2020 - cambridge.org
This article presents an overview of the recent standardization activities for point cloud
compression (PCC). A point cloud is a 3D data representation used in diverse applications …
compression (PCC). A point cloud is a 3D data representation used in diverse applications …
Deep problems with neural network models of human vision
Deep neural networks (DNNs) have had extraordinary successes in classifying
photographic images of objects and are often described as the best models of biological …
photographic images of objects and are often described as the best models of biological …
Motion planning and control for mobile robot navigation using machine learning: a survey
Moving in complex environments is an essential capability of intelligent mobile robots.
Decades of research and engineering have been dedicated to developing sophisticated …
Decades of research and engineering have been dedicated to developing sophisticated …
Efficient structure from motion for large-scale UAV images: A review and a comparison of SfM tools
Unmanned aerial vehicle (UAV) images have gained extensive attention in varying fields,
and the Structure from Motion (SfM) technique has become the gold standard for aerial …
and the Structure from Motion (SfM) technique has become the gold standard for aerial …
Automated pixel-level pavement distress detection based on stereo vision and deep learning
Automated pavement distress detection based on 2D images is facing various challenges.
To efficiently complete the crack and pothole segmentation in a practical environment, an …
To efficiently complete the crack and pothole segmentation in a practical environment, an …
Structure from motion photogrammetry in physical geography
MW Smith, JL Carrivick… - Progress in physical …, 2016 - journals.sagepub.com
Accurate, precise and rapid acquisition of topographic data is fundamental to many sub-
disciplines of physical geography. Technological developments over the past few decades …
disciplines of physical geography. Technological developments over the past few decades …