Results 151 to 160 of about 26,254 (190)

Synthetic Data Enhancement and Network Compression Technology of Monocular Depth Estimation for Real-Time Autonomous Driving System. [PDF]

Sensors (Basel)
Jun W, Yoo J, Lee S.
europepmc   +1 more source

Expanding Sparse Radar Depth Based on Joint Bilateral Filter for Radar-Guided Monocular Depth Estimation. [PDF]

Sensors (Basel)
Lo CC, Vandewalle P.
europepmc   +1 more source

Dense monocular depth estimation for stereoscopic vision based on pyramid transformer and multi-scale feature fusion. [PDF]

Sci Rep
Xia Z, Wu T, Wang Z, Zhou M, Wu B, Chan CY, Kong LB.   +6 more
europepmc   +1 more source

Robust Regression for Monocular Depth Estimation

, 2021
Lienen, Julian, Nommensen, Nils, Ewerth, Ralph, Hüllermeier, Eyke   +3 more
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Perceptual Monocular Depth Estimation

Neural Processing Letters, 2021
Monocular depth estimation (MDE), which is the task of using a single image to predict scene depths, has gained considerable interest, in large part owing to the popularity of applying deep learning methods to solve “computer vision problems”. Monocular cues provide sufficient data for humans to instantaneously extract an understanding of scene ...
Janice Pan, Alan C. Bovik
openaire   +1 more source

Monocular Depth Estimation (Literature Review)

The EYE GLAZ, 2022
Background. The physiological basis of spatial perception is traditionally attributed to the binocular system, which integrates the signals coming to the brain from each eye into a single image of the three-dimensional outside world. The perception of three-dimensionality, however, is also possible due to the evolutionarily older monocular system of ...
S. I. Rychkova, V. G. Likhvantseva
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Monocular depth estimation network with single-pixel depth guidance

Optics Letters, 2023
Due to the scale ambiguity problem, the performance of monocular depth estimation (MDE) is inherently restricted. Multi-camera systems, especially those equipped with active depth cameras, have addressed this problem at the expense of increased hardware costs and space.
Hongjae Lee, Jinbum Park, Wooseok Jeong, Seung-Won Jung   +3 more
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Monocular Depth Estimation Using Relative Depth Maps

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
We propose a novel algorithm for monocular depth estimation using relative depth maps. First, using a convolutional neural network, we estimate relative depths between pairs of regions, as well as ordinary depths, at various scales. Second, we restore relative depth maps from selectively estimated data based on the rank-1 property of pairwise ...
Jae-Han Lee, Chang-Su Kim
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