1. Dr. 官順暉 (Drake Guan)
超解析度影片成像技術
(Video Super Resolution)
# Machine Learning # Generative AI
2. ● KKCompany Technologies
AI Research
● BlendVision (KKStream)
Video Encoding System
Recommender System
● Digimax Inc.
Animation Pipeline
3-D Rendering & Pipeline
● National Taiwan University
Computer Graphics
Computational Photography
16. Single Image Super Resolution (SISR / SR)
IPHONE PHOTOS ZOOM LIMIT EXTENDED IN IOS 14 (+INFINITE ZOOM TRICK), iPhoneTricks
17. Single Image Super-Resolution from Transformed Self-Exemplars,
CVPR 2015
A+: Adjusted Anchored Neighborhood Regression for Fast Super-
Resolution, ACCV 2014
Machine Learning based
18. ● SRCNN (2014): the first deep-learning model
● SRGAN (2017): adopting Generative Adversarial Network
● EDVR (2019): CVPR NTIRE Challenge champion
● BasicVSR++ (2021): advanced deep learning model for high-quality video super-resolution
● Real-ESRGAN (2021): applied on real-world low-res images
● SwinIR (2021): utilizing Transformer model
● CodeFormer (2022): blind face restoration/enhancement
● STDO (2023): divide-n-conquer + lite model on mobile devices
● …
Learning a Deep Convolutional Network for Image Super-Resolution, ECCV 2014
Deep Learning based
30. SD full-HD 4K 8K
30 fps 60 fps 120 fps
SDR 100 nits HDR 1000 nits HDR 4000 nits SDR to HDR
Color gamut conversion
Color depth booster
Video Super Resolution
Video Frame Interpolation
8 bits 10 bits 12 bits
BT709 P3 BT2020
Resolution
Color gamut
Frame rate
Dynamic range
Bit depth
VSR 發展方向
31. 1. Enhancing Video Quality: Video super
resolution techniques are used to
enhance the quality of low-resolution
videos. By increasing the resolution, these
techniques can produce sharper and
clearer videos, making them more
enjoyable to watch.
2. Surveillance Systems: Video super
resolution plays a crucial role in
surveillance systems, where low-res
surveillance footage often hampers the
ability to identify people or objects
accurately. By SR, the quality of the
captured video can be improved, aiding
in forensic analysis and identification.
3. Video Compression: Video super
resolution can be used in video
compression algorithms to reduce the file
size while maintaining a high-quality
viewing experience. By upscaling low-
resolution videos before compression, the
compressed video can retain more
details, resulting in a better visual
representation.
4. Virtual Reality (VR) and Augmented
Reality (AR): Video super resolution is
important in VR and AR applications to
provide a more immersive experience. By
enhancing the resolution of video
content, users can perceive more detailed
and realistic virtual environments, leading
to a more engaging and believable exp.
5. Broadcast and Streaming Services:
Video super resolution is utilized in
broadcast and streaming services to
upscale low-resolution content to higher
resolutions. This allows for the
distribution of content in various formats
while maintaining a consistent and
visually appealing quality across different
devices and platforms.
6. Medical Imaging: Video super
resolution has applications in medical
imaging, such as enhancing the quality of
low-resolution videos captured during
surgeries or medical procedures. This can
aid medical professionals in making
accurate diagnoses and treatment
decisions.
7. Video Restoration: Video super
resolution techniques can be employed
in video restoration applications to repair
and enhance old or degraded video
footage. By upscaling and enhancing the
resolution, it is possible to recover lost
details and improve the overall visual
quality of the restored video.
8. Digital Zoom: In applications where
digital zoom is utilized, video super
resolution can enhance the zoomed-in
portions of the video. By increasing the
resolution, the details in the zoomed
region can be better preserved, resulting
in a clearer and more informative image.
ChatGPT: VSR 的應用?