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Intro
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Classroom Contents
Learning Robust Imaging Models without Paired Data
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- 1 Intro
- 2 Outline
- 3 Linear approximation for imaging process
- 4 The error effects
- 5 Model based approaches
- 6 Deep learning (DL) based approaches
- 7 Data bottleneck in DL
- 8 Data collection in video superresolution
- 9 Goal of the talk
- 10 Image denoising
- 11 The basic idea
- 12 Model formulation
- 13 Numerical method
- 14 One remark on overfitting issue
- 15 Quantitative results for real noisy images
- 16 Qualitative results
- 17 Latent space verification
- 18 Real-world noisy images from Huawei
- 19 Image segmentation
- 20 Probabilistic model
- 21 Examples
- 22 Deep CV model
- 23 Distributions in latent space
- 24 Motivation
- 25 The case of unpaired datasets
- 26 Unpaired degradation modeling
- 27 The idea
- 28 The loss function
- 29 Inference invariant condition
- 30 Synthetic noisy images
- 31 Experiments
- 32 Visual results
- 33 Summary
