Video Super-Resolution: Approaches to modelling and evaluation
Andrey Lukyanenko
CV R&D Lead, MTS AI
Content
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What is Video Super-Resolution
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Approaches to Single Image Super-Resolution
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Approaches to Video Super-Resolution
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Real-Time Video Super-Resolution
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Real-World Video Super-Resolution
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Evaluation: metrics and datasets
About me
- Economist
- ~4 years as ERP-consultant
- ~8 months self-study
- ~5 years as Data Scientist
- Tech Lead in R&D in Computer Vision @ MTS AI
- Kaggle Competition Master, Notebook top-1, Discussion Grandmaster
VSR: definition
- Video super-resolution is the task of upscaling a video from a low-resolution to a high-resolution.
- Multiple solutions for the same LR image
VSR: definition
VSR: depiction
VSR: usage examples
VSR: usage examples
VSR: usage examples
VSR: usage examples
VSR: usage examples
SR, IR, IE
SISR
SISR
SISR
SISR
Nearest-neighbor Interpolation
Bilinear interpolation
Bicubic interpolation
SRCNN
SRCNN
VDSR
FSRCNN
ESPCN
EDSR
Recursive networks
DRCN
LapSRN
SRGAN
ESRGAN
Diffusion models
Diffusion models
SwinIR
SwinIR
VSR
VSR
MEMC
Deep-DE
TecoGAN
Deformable Convolution
Deformable Convolution
EDVR
EDVR
FFCVSR
3DSRnet
3DSRnet
STCN
PFNL
CARN
CARN
FAST
RSISR
RSISR
BSR
RSISR: self-supervised
Datasets
Datasets
Metrics
- Pairwise metrics
- Image quality metrics
- Human evaluation
Pairwise preference
- Choose what is better: Original and SR
- No external distractions
- The same setup
- Check the participants
Conclusions
- Many approaches, no free lunch
- No best metric
- Worse performance in real-world
- Multiple degradations
- Low performance for extreme SR (x16 and higher)
- Requires a lot of VRAM
References
References
References
- https://arxiv.org/abs/2103.14006
- https://arxiv.org/pdf/2007.12928.pdf
- https://www.analyticsvidhya.com/blog/2021/05/deep-learning-for-image-super-resolution/
- https://github.com/ChaofWang/Awesome-Super-Resolution
- https://github.com/LoSealL/VideoSuperResolution
- https://arxiv.org/pdf/2107.03055.pdf
- https://github.com/Thmen/EGVSR
- https://arxiv.org/ftp/arxiv/papers/2107/2107.05307.pdf
- https://ai.googleblog.com/2021/07/high-fidelity-image-generation-using.html
- https://developer.huawei.com/consumer/en/hiai/engine/image-super-resolution/
References
- https://www.techeblog.com/nvidia-ai-research-maxine-video-calls-conference/
- https://www.theverge.com/2019/12/17/21025811/ai-super-resolution-zoom-enhance-pixelmator-pro
- https://bitmovin.com/wp-content/uploads/2020/05/Super-Resolution.006-1-e1590143447660.jpeg
- https://dmitryulyanov.github.io/deep_image_prior
- http://www.mit.edu/~sze/fast.html
- https://www.imageeprocessing.com/2017/11/nearest-neighbor-interpolation.html
- https://theailearner.com/2018/12/29/image-processing-bilinear-interpolation/
- https://towardsdatascience.com/deformable-convolutions-demystified-2a77498699e8
Contacts
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ods.ai @artgor
vsr_iitg
By Andrey Lukyanenko
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