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Globally and locally semantic colorization via exemplar-based broad-GAN
Haoxuan Li
, Bin Sheng
,
Ping Li
, Riaz Ali
, C. L. Philip Chen
Department of Computing
The Hong Kong Polytechnic University
Research output
:
Journal article publication
›
Journal article
›
Academic research
›
peer-review
62
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Citations (Scopus)
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Dive into the research topics of 'Globally and locally semantic colorization via exemplar-based broad-GAN'. Together they form a unique fingerprint.
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Keyphrases
Generative Adversarial Networks
100%
Colorization
100%
Exemplar-based
100%
Target Image
66%
Global-local
33%
Color Image
33%
Sparse Representation
33%
Broad Learning System
33%
State-of-the-art Techniques
16%
Dictionary
16%
Grayscale Image
16%
Color Information
16%
Self-similarity
16%
Network Framework
16%
Local Structure
16%
Feature Extracting
16%
Semantic Structure
16%
Training Stability
16%
Semantic Features
16%
Semantic Content
16%
Semantic Similarity
16%
Image Colorization
16%
Natural-looking
16%
Global Semantics
16%
Matching Consistency
16%
Local Affinity
16%
Conditional Generative Adversarial Network (cGAN)
16%
Perceptual Information
16%
Challenging Problems
16%
Affinity Energy
16%
Similarity Constraint
16%
Dictionary-based
16%
Computer Science
Generative Adversarial Networks
100%
Subnet
100%
Reference Image
60%
Sparse Representation
40%
Broad Learning System
40%
Subnetwork
20%
Color Information
20%
Global Constraint
20%
Semantic Feature
20%
Local Affinity
20%
Perceptual Information
20%
Extracted Feature
20%
Local Structure
20%
Conditional Generative Adversarial Network
20%