Depth estimation improvement in 3D integral imaging using an edge removal approach
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DOI: 10.1007/s10044-018-0721-4
Abstract: AbstractA new depth estimation method for 3D reconstruction in a synthetic aperture integral imaging framework is presented. This method removes the edges of the objects in the elemental images when the objects are in focus.… read more here.
Keywords: estimation improvement; integral imaging; depth estimation; improvement integral ... See more keywords
Self-supervised Monocular Trained Depth Estimation Using Triplet Attention and Funnel Activation
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DOI: 10.1007/s11063-021-10608-5
Abstract: Dense depth estimation based on a single image is a basic problem in computer vision and has exciting applications in many robotic tasks. Modelling fully supervised methods requires the acquisition of accurate and large ground… read more here.
Keywords: self supervised; estimation; depth estimation; triplet attention ... See more keywords
Monocular depth estimation based on deep learning: An overview
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DOI: 10.1007/s11431-020-1582-8
Abstract: Depth information is important for autonomous systems to perceive environments and estimate their own state. Traditional depth estimation methods, like structure from motion and stereo vision matching, are built on feature correspondences of multiple viewpoints.… read more here.
Keywords: depth; monocular depth; depth estimation; deep learning ... See more keywords
Real-to-virtual domain transfer-based depth estimation for real-time 3D annotation in transnasal surgery: a study of annotation accuracy and stability
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Computer Assisted Radiology and Surgery"
DOI: 10.1007/s11548-021-02346-9
Abstract: Surgical annotation promotes effective communication between medical personnel during surgical procedures. However, existing approaches to 2D annotations are mostly static with respect to a display. In this work, we propose a method to achieve 3D… read more here.
Keywords: surgery; depth estimation; accuracy; annotation ... See more keywords
Improving snow depth estimation by coupling HUT-optimized effective snow grain size parameters with the random forest approach
Sign Up to like & getrecommendations! Published in 2021 at "Remote Sensing of Environment"
DOI: 10.1016/j.rse.2021.112630
Abstract: Abstract Snow cover is highly critical for global water and energy cycles because of its wide areal extent, high reflectivity and good thermal insulation. Knowledge of snow conditions, e.g., snow water equivalent (SWE) and snow… read more here.
Keywords: snow; approach; model; snow depth ... See more keywords
An Adaptive Unsupervised Learning Framework for Monocular Depth Estimation
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DOI: 10.1109/access.2019.2946323
Abstract: Depth estimation from a single image plays an important role in 3D scene perception. Owing to the development of deep convolutional neural networks (CNNs), monocular depth estimation models have achieved a large number of exciting… read more here.
Keywords: depth; model; monocular depth; adaptive unsupervised ... See more keywords
Leveraging Contextual Information for Monocular Depth Estimation
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DOI: 10.1109/access.2020.3016008
Abstract: Humans strongly rely on visual cues to understand scenes such as segmenting, detecting objects, or measuring the distance from nearby objects. Recent studies suggest that deep neural networks can take advantage of contextual representation for… read more here.
Keywords: depth estimation; depth; estimation; monocular depth ... See more keywords
D-Net: A Generalised and Optimised Deep Network for Monocular Depth Estimation
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DOI: 10.1109/access.2021.3116380
Abstract: Depth estimation is an essential component in computer vision systems for achieving 3D scene understanding. Efficient and accurate depth map estimation has numerous applications including self-driving vehicles and virtual reality tools. This paper presents a… read more here.
Keywords: depth; deep network; estimation; net ... See more keywords
Learning Depth Estimation From Memory Infusing Monocular Cues: A Generalization Prediction Approach
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DOI: 10.1109/access.2022.3151108
Abstract: Depth estimation from a single image is a challenging task, yet this field has a promising prospect in automatic driving and augmented reality. However, the prediction accuracy is degraded significantly when the trained network is… read more here.
Keywords: depth estimation; learning depth; prediction; memory ... See more keywords
Towards Monocular Neural Facial Depth Estimation: Past, Present, and Future
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DOI: 10.1109/access.2022.3158950
Abstract: This article contains all of the information needed to conduct a study on monocular facial depth estimation problems. A brief literature review and applications on facial depth map research were offered first, followed by a… read more here.
Keywords: depth estimation; depth; loss; neural facial ... See more keywords
A Robust Light-Weight Fused-Feature Encoder-Decoder Model for Monocular Facial Depth Estimation From Single Images Trained on Synthetic Data
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DOI: 10.1109/access.2023.3267970
Abstract: Due to the real-time acquisition and reasonable cost of consumer cameras, monocular depth maps have been employed in a variety of visual applications. Regarding ongoing research in depth estimation, they continue to suffer from low… read more here.
Keywords: depth; depth estimation; model; encoder ... See more keywords