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Study mode:
on
1
Intro
2
Motivation
3
pix2pix Baseline
4
Improving Photorealism and Resolution: Coarse to Fine Genera
5
Improving Photorealism and Resolution: Multi-Scale Discriminators
6
Using Instance Maps
7
Learning an Instance Level Feature Embedding
8
Results: Quantitative Comparison
9
Results: Perceptual Study
10
Results: Human Perceptual Study - Unlimited Tin
11
Results: Human Perceptual Study - Limited Time
12
Results: Generator Comparison
13
Results: Discriminator Comparison
14
Interactive Object Editing
Description:
Explore high-resolution image synthesis and semantic manipulation using conditional GANs in this 34-minute lecture from the University of Central Florida. Delve into the pix2pix baseline and learn techniques for improving photorealism and resolution through coarse-to-fine generation and multi-scale discriminators. Discover the use of instance maps and the process of learning instance-level feature embeddings. Examine quantitative comparisons, perceptual studies, and human evaluations of generated images. Compare generator and discriminator performances, and gain insights into interactive object editing capabilities.

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

University of Central Florida
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