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Initialization and Alignment for Adversarial Texture Optimization
Xiaoming Zhao
,
Zhizhen Zhao
,
Alexander G. Schwing
Electrical and Computer Engineering
Coordinated Science Lab
Statistics
Mathematics
Carl R. Woese Institute for Genomic Biology
National Center for Supercomputing Applications (NCSA)
Siebel School of Computing and Data Science
Research output
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Chapter in Book/Report/Conference proceeding
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Keyphrases
Texture Optimization
100%
Texture Generation
66%
Image Dataset
66%
Alignment Method
33%
Well-aligned
33%
Sharpness Evaluation
33%
Misalignment
33%
Complex Geometry
33%
Low Quality Data
33%
Video Data
33%
Handheld Devices
33%
Texture Evolution
33%
Computer Vision Methods
33%
Texture Map
33%
Relative Improvement
33%
Image Alignment
33%
Hard Assignment
33%
Robust Mapping
33%
Perceptual Measurement
33%
Computer Science
Low Data Quality
100%
Handheld Device
100%
Image Alignment
100%
Computer Vision
100%
Mathematics
Classical Method
100%
Image Data
100%
Complex Geometry
100%