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Multiscale Attention Fusion for Depth Map Super-Resolution Generative Adversarial Networks [PDF]
Entropy, 2023 Color images have long been used as an important supplementary information to guide the super-resolution of depth maps. However, how to quantitatively measure the guiding effect of color images on depth maps has always been a neglected issue.
Dan Xu, Xiaopeng Fan, Wen Gao
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Depth Map Upsampling via Multi-Modal Generative Adversarial Network [PDF]
Sensors, 2019 Autonomous robots for smart homes and smart cities mostly require depth perception in order to interact with their environments. However, depth maps are usually captured in a lower resolution as compared to RGB color images due to the inherent ...
Daniel Stanley Tan +4 more
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A Systematic Comparison of Depth Map Representations for Face Recognition [PDF]
Sensors, 2021 Stefano Pini +2 more
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Depth Estimation Based on Scene Object Attention and Depth Map Fusion [PDF]
Jisuanji gongcheng, 2023 The existing monocular depth estimation algorithm mainly obtains stereo information from a single image.This approach leads to blurred details of adjacent depth edges and apparent missing objects.A monocular depth estimation algorithm based on scene ...
WEN Jing, YANG Jie
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Monocular Depth Estimation Based on Multi-Scale Depth Map Fusion
IEEE Access, 2021 Monocular depth estimation is a basic task in machine vision. In recent years, the performance of monocular depth estimation has been greatly improved. However, most depth estimation networks are based on a very deep network to extract features that lead
Xin Yang +4 more
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Depth Map Refinement for Immersive Video
IEEE Access, 2021 In this article, we propose a depth map refinement method that increases the quality of immersive video. The proposal highly enhances the inter-view consistency of depth maps (estimated or acquired by any method), crucial for achieving the required ...
Dawid Mieloch +2 more
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Depth Map Super-Resolution Using Guided Deformable Convolution
IEEE Access, 2021 Depth maps acquired by low-cost sensors have low spatial resolution, which restricts their usefulness in many image processing and computer vision tasks.
Joon-Yeon Kim +4 more
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Depth Map Super-Resolution via Cascaded Transformers Guidance
Frontiers in Signal Processing, 2022 Depth information captured by affordable depth sensors is characterized by low spatial resolution, which limits potential applications. Several methods have recently been proposed for guided super-resolution of depth maps using convolutional neural ...
Ido Ariav, Israel Cohen
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Estimation of Soil Surface Roughness Using Stereo Vision Approach
Sensors, 2021 Soil roughness is one of the most challenging issues in the agricultural domain and plays a crucial role in soil quality. The objective of this research was to develop a computerized method based on stereo vision technique to estimate the roughness ...
Afshin Azizi +4 more
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Perspectives of RealSense and ZED Depth Sensors for Robotic Vision Applications
Machines, 2022 This review paper presents an overview of depth cameras. Our goal is to describe the features and capabilities of the introduced depth sensors in order to determine their possibilities in robotic applications, focusing on objects that might appear in ...
Vladimir Tadic +7 more
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