Khan et al., 2021 - Google Patents

A review of benchmark datasets and training loss functions in neural depth estimation

Khan et al., 2021

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Document ID
14172598095107602271
Author
Khan F
Hussain S
Basak S
Moustafa M
Corcoran P
Publication year
Publication venue
IEEE Access

External Links

Snippet

In many applications, such as robotic perception, scene understanding, augmented reality, 3D reconstruction, and medical image analysis, depth from images is a fundamentally ill- posed problem. The success of depth estimation models relies on assembling a suitably …
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Classifications

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    • G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06T7/00—Image analysis
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    • G06T2207/10024—Color image
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    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
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    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
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