As shown above, from 100x133PIx to 400x532PIx, what does it mean to have technology that can increase resolution by 400%, besides being visually clear?
It means:
- Old photos, old movies, animation and other picture quality can be quickly improved, the resolution of free adjustment
- The effect of industrial algorithms can be greatly improved with the improvement of data quality
- You can also quickly view hd videos or pictures when the network signal is poor
- Image transmission bandwidth and storage space will be greatly compressed, transmission costs will be greatly reduced
Images are quoted from public data sets [1][2][3]
Make the world more clearly is not magic, but a technique known as the super-resolution ascension (hereinafter referred to as “super”), to the low-resolution image, video, through feature extraction, feature fusion, image reconstruction and the sampling (Pix – Shuffle), restore and make up the information lost and eventually into high resolution image and video.
There are many ways to realize the super segmentation, and the peak signal to noise ratio PSNR32.53, structure similarity SSIM0.9083 video super segmentation algorithm pp-msvsr, with its excellent performance SOTA industry!
Without further ado, let’s directly look at the comparison chart of PP-MSVSR’s performance (peak-to-noise ratio, structural similarity) with other algorithms on the authoritative data set of video hyperpartition:
The source code and tutorials for PP-MSVSR have also been open sourced to the PaddleGAN project. In addition to video hyperscoring, PaddleGAN also provides industry-leading single-image hyperscoring algorithms. The heart is better than the action, quickly Star⭐ collection start to try github.com/PaddlePaddl… 1. Change old movies from fuzzy to clear, and realize image restoration
In the field of entertainment, such as social networking, news media, e-commerce and other industries, it is often involved in video enhancement and editing, and THE performance of PP-MSVSR is really commendable.
2, By improving the clarity of training data, the algorithm accuracy is improved
Whether it is target detection, image recognition, image classification, semantic segmentation and other CV related tasks, the quality of training data has a great impact on the final task effect. Therefore, developers can use PP-MSVSR to improve the video data at any resolution to the ideal resolution to achieve the accuracy of downstream detection, recognition, segmentation and other tasks.
Images are taken from a public data set [4][5]
3, reduce the cost of video network transmission algorithm is used in the terminal to restore ascension resolution in this era of has ultimate pursuit on resolution, video storage and transmission cost is higher and higher, for example, 4 k signal transmission, transmission cost at least several thousand yuan a day, if you want to give the cost to a “lower”, must be from the storage and transmission. With the help of video super sub, the video cloud storage space can be greatly reduced, further reduce the video CDN transmission bandwidth ****, and improve the video transmission speed, which means that while the storage space and transmission cost are greatly reduced, the video transmission speed has also been significantly increased!
Pp-msvsr is so useful, is it complicated to use? The answer is: not at all!The resolution can be improved with just one command!
Image quoted from public data set [1]
PaddleGAN also provides a variety of cutting-edge GAN-related capabilities and applications, including image generation, lip synthesis, face fusion, etc. What are you waiting for? Get started at Star⭐! Github.com/PaddlePaddl…
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