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Study mode:
on
1
Intro
2
Goal
3
Contemporary problems
4
Contribution
5
Approach
6
Stage 1 - Mask generator GM
7
Stage 2 - Image inpainter G
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Architecture - Mask generator
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Architecture - Image inpainter
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Training - Mask generator
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Training - Image inpainter
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Mask priors
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Mask generator loss
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Final loss function - Mask genera
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Optimizing inpainter - local labe
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Final loss function - Image inpair
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Dataset - 1
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Evaluation metrics
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Removal performance
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Image quality assessment
21
Human evaluation
22
Quantitative results
23
Failure cases
24
Ablation study - 1
Description:
Learn about a novel approach to automatic object removal in images using weak supervision in this 30-minute lecture from the University of Central Florida. Explore the two-stage process involving a mask generator and image inpainter, delving into their architectures, training methods, and loss functions. Examine the dataset used, evaluation metrics, and quantitative results, including removal performance and image quality assessment. Gain insights into potential failure cases and the findings from ablation studies in this comprehensive overview of adversarial scene editing techniques.

Adversarial Scene Editing: Automatic Object Removal from Weak Supervision

University of Central Florida
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