PULSE is a new image upsampling algorithm. This new algorithm transforms a blurry image into a high-resolution image.
It can take a super low-resolution 16x16 image and turn it into a 1080p high-definition human face! You don’t believe me? Then you can try it yourself in less than a minute using their demo.
Watch the video
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Video Transcript
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this new algorithm transforms a blurry
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image to a high-resolution image it can
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take a super low resolution like a 16 by
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16 image and turn it into a 1 ADP High
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Definition human face you don't believe
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me then you can do just like me and try
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it yourself in less than a minute but
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first let's see how they did that this
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is what they I and I share artificial
00:27
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00:33
to not miss any further news to start we
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have to introduce the concept of photo
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up sampling our image super resolution
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the goal here is to construct a high
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resolution image from a correspondingly
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low resolution input which is a face in
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this case the low resolution will be
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such as 16 by 16 pixels super blurry to
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a high definition on one a DP image with
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a clear face usually these techniques
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use supervised learning to trained our
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network and measure the average distance
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between the new high-definition image
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and a high resolution ground truth but
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using this technique seem to neglect
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important details like textures and
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create some blurry spots when the answer
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is uncertain because of the differences
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between the low and high resolutions
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this is where polls comes and play their
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goal was to generate realistic images
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within the set of plausible solutions
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meaning that they wanted to rely on an
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actual image that was realistic where
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it's downscale version will look the
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same as the original low resolution
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image instead of having to guess
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directly from the low resolution image
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so they introduced a new self supervised
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technique that traverses the high
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resolution natural image manifold
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searching for images that don't scale to
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the original low resolution image this
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is great because as you can see in this
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image multiple high resolution images
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can be done scaled to the same low
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resolution image which will cause a
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blurry uncertainty with previous
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techniques these high resolution images
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are made by a gun Network which is pre
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trained in an unsupervised way to
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generate multiple realistic and sharp
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face images
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if you are not familiar with self
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supervised learning or generative
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adversarial networks or Ganz I invite
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you to watch the video I introduced them
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both are linked in the description below
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at first I was skeptical probably just
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like you so I decided to try it myself
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since the code is available and the
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results were amazing you can set the
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image is super blurry no one could guess
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how I really looked like in this picture
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and yet even though I don't think it
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looks just like me it's still extremely
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close to the reality for the amount of
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information it was fed you can even try
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it on yourself right now with the demo
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no setup needed and it takes only a
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minute or so click on the link in the
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description run the program enter your
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image which will not be saved by them
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for privacy and here are the results in
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this work they used a Celebi HQ data set
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which is a large scale face attribute
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data set with more than 200 thousand
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celebrity images this could explain why
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the faces look older and different than
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non celebrity faces it will be
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interesting to see a comparison with
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another large data set using a different
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segment of the population and this work
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is of course generalizable and could be
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of great use in fields like medicine
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astronomy or satellite imagery where
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sharp and high-resolution images are
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difficult to have due to their cast or
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hardware and memory limitations of
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course this was just a simple overview
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of the pulse photo op sampling algorithm
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I strongly recommend to read the paper
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and play with the code both are linked
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in the description for more information
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leave a like if you went this far in the
03:52
video and since there are over 90% of
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subscribed yet please consider
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