This AI Performs Super Resolution in Less Than a Second

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Moby Motion : Unbelievable. Fast computation is crucial for this technology to see mainstream use - especially since lots of people might want to use it on videos and get rid of 480p once and for all

kastakan : Finally we'll be able to watch Japanese porn! :D

Ville Pakarinen : I love how he always calls me a "fellow scholar" even though I don't do shit

Krishna Mohan : Ok. Time to stop buying 1000$ phones. Thanks AI. Just don't kill me in the future.

Catalepsy : Like those tv shows and movies "Enhance that" 🤣

phreakinpher : ENHANCE!

CookingAndJava : Finally the police will actually be able to enhance low resolution surveillance camera footage, like in the movies!

John Doe : Enhance 224 to 176. Enhance. Stop. Move in. Stop. Pull out, track right, stop. Center and pull back. Stop. Track 45 right. Stop. Center and stop. Enhance 34 to 36. Pan right and pull back. Stop. Enhance 34 to 46. Pull back. Wait a minute. Go right. Stop. Enhance 57-19. Track 45 left. Stop. Enhance 15 to 23. Give me a hard copy right there.

Menyhért Márton : What happens when you overdo the up-scaling? I'm curious if these algorithms produce distorted or unrealistic images.

Bob Salita : GitHub:

sabo fx : *N O F U C K I N G W A Y* !!! This is really amazing! Cannot wait for the photoshop filter! Thanx m8!

Lurker1979 : The print industry will love this. Heck as a photographer I will love this option. Instead of having to cram more and more megapixels on to a chip and making more artifacts. Why not do this instead. Upscale a 20 megapixel image to 50 instead. I could even see this being applied to video. How cool would it be to have a old 60s sitcom that was filmed with TV cameras and has no film and upscale it to full HD.

21EC : oh wow....this in realtime could be used for an old game like Doom...the game is really pixelated, so it could be pretty cool to play it with higher res' graphics.

Reavenk : Great results! The intermediary results look like bilateral blur but then it gets really sharp and detailed really fast. There's some bilaterial blurish areas in some of the final iterative results, but you have to really be looking for it.

movax20h : Wow. Amazing technique. Almost magic. It puts details in the image that were not there before. The aligator picture ( 2:22 ) is amazing. You can see that the higher resolution picture has amazing detailed textures that were just smooth color with just few pixels and no texture at all. The algorithm learned what the texture should be based on other surranding features. Magic. There are some minor artifacts in one scene, at 1:41 , the landscape photo of a Greek(?) town with sea - the rocks in bottom right corner gets some additional high frequency texture, which doesn't feel natural. It can be also used as a possibly better subsitute for deconvolutional algorithms, to remove bluring, i.e. due to inaccurate focus. Greate video. Would be nice to mention how it actually works. I guess it is a convolutional deep neural network, so 5 second slide with architecture of the network would be useful.

Jordan Scarrott : When you quote the time it takes to process these images, do these times not depend on the hardware they're running on? Is there an industry standard for this in this field? I don't know what to make of these times. I love the videos by the way. Really quality stuff

M Siemons : As a physicist let me remark: the upsampling and making up new pixels is very nice, it is NOT super resolution. Resolution of an image is very well defined in terms of the diffraction limit (the largest spatial frequency transmitted by your imaging system) and there are ways to overcome thus limit with super resolution imaging techniques (often in microscopy). AI does not improve this resolution, but should be seen as a smart interpolation of data/pixels.

Riyad : amazing, and all this time we were making fun of csi:miami enhance that licence plate scenes.

skierpage : I don't think the AI uses related images to supersample, paper says "All presented models are trained with the DIV2K [34] training set, which contains 800 high-resolution images." If that set includes lots of alligator pictures then the results seem unfair 🙂. But what if the neural network recognize the kind of source picture and then supersampled based on related high-res images? Find higher-resolution pictures of fox fur or alligator skin or that particular village and supersample from training based off that.

Facebotter : Can't wait to see a similar technique used with audio. We'll be able to watch full-fledged movies from the past as if they were filmed today!

Dariush MJ : Like if you watched in 144p

Anton Johansson : Did you have any success on images that werent first down sampled? It (quite reasonably) doesn't like JPEG.

21EC : damn....thats beyond crazy ! its like magic. but when do you think we will see this being used in for example google images...?

Nick Fotopoulos : I can't wait to use this on my old photos, videos, and movies!

Shall NotWither : This will definitely create legal problems for the photo industry and copyright in the short term as removing watermarks and enhancing images. Not to mention a future when you can download a low resolution video and then upscale it to HD while enjoying copyright free images because the AI only approximated the video. Amazing.

21EC : perhaps this could also be used in video games...I mean in the future when theyll make this work in realtime

Lagraig O'Moof : Up to 8 times? Doesn't JPEG use 8x8 blocks within an image? This means that an 8x downscaled JPEG file ought to be equivalent to an 8x downscaled version of the original raw image, and so JPEGs would be ideal to train a network like this. i.e. Downscale JPEG 8x as raw pixels, upscale to 8x with the network as a raw image, apply JPEG compression to the output and then compare the 8x8 blocks between the original JPEG and the output.

Aadit Doshi : Looks like CSI was just way ahead of its time. ENHANCE!

Neoshaman Fulgurant : Next step, do it under .2ms on a tegra GPU, better a Mali 400mp. Then gaming is changed forever. Next step, take a low quality render turn it into cg.

dkwroot : This could be awesome if it gets implemented in 3D rendering. A scene could be rendered using 50% resolution and then scaled up in real time using super resolution.

HebaruSan : I hope someday that we will be able to feed into an AI the first two Star Wars movies and have it output better prequels.

Cynosure : I watched it in 144p and was wondering why I couldn't see the differences

Niko Craft : put this into Unity and Unreal Engines plus enable full raytracing = real time raytracing and most realistic graphics!

CooleoBrad : Wow. "Zoom. Enhance." might actually be feasible now!

Alex4Lolz : Are there any practical projects like a website or software that uses this except for "Let's enhance". I've found their results to be pretty lack luster.

Squares : I'd like to see the result on a very low quality image coming from the crop of street webcam ! Like in the movies :)

Max Musterman : thx a lot for making all of those wonderful videos and i will watch every video from you. But it feels like you focus a lot on the visual/grafics area of ai. But i think there are a lot more fields in wich ai is used, in wich i am also very interested. love you whatever you focus on. would also love recommendations of other two minute paper-like ressources. Never forget: what an awesome time to be alife!

Armuotas : Astronomers will be tripping about this! (Exo)planet and asteroid surface mapping, galaxy deep fields, proplids, etc.

Name : Isn't nvidia's DLSS basically this but in real time?

André Pfitzner : When the processing power allows it to be integrated in super resolution TVs they will sell more.

Zerofever : "enhance" used to be a meme, now its real!

Asenstiven Odin Other : Translation (RUS) Moby Motion Невероятно. Быстрое вычисление имеет решающее значение для этой технологии, чтобы увидеть основное использование - тем более, что многие люди могут захотеть использовать его на видео и избавиться от 480p раз и навсегда Vlad Kostin для видео вам понадобятся специальные временные когерентные варианты этой техники David Hagler Я предполагаю, что без временной согласованности вы по существу видите шум между двумя кадрами, уменьшая общее кажущееся разрешение до чего-то близкого к исходному материалу? Joe Ch Я бы назвал это революционным IF временным, и согласованность VR была бы там. Видеоролики VR особенно дороги, потому что вам необходимо передать (или сделать рендер для начала!) Достаточно пикселей для 360 просмотров на каждый глаз. Он также имеет потерянную избыточную потенциально вычитаемую информацию. Таким образом, это принесло бы большую пользу от сверхразрешения от ИИ. Но если вы галлюцинировали разные пиксели на глаз, то это сделало бы невозможным применение для контента VR, даже если существует временная согласованность. У NVidia denoiser было одно и то же. Я попытался использовать его для контента, переданного с помощью Arnold, и он даже говорит в документации, чтобы не использовать его для видео, потому что он будет мерцать.

LanYarD : 2:47 BOI

Wild Animal Channel : But does it create fake images? So shouldn't be used for news reports. Or it would be fake news!

William Taylor : it's weird why it's crooked, it's like they were shaking the camera. Bars aren't left then right then left, go, oh, bars are straight. surely, even shaking the camera, the shutter speed doesn't matter, all the light hit at the same time. first you have implied hue direction, then gamut falloff, that's four times. I gotta think of some spooky shadow detection for the bars trick. Your really looking for a three standard deviation improvement. So you got green 0 to 255, now 40 would be way to noticable. it might be another object, but 120 has to be the same object. So you got any 9 points with RGB. The fox has no improvement, but I can see how each whispy tuft should have a solid grey, 124,124,124. This is where gamut augmentation comes in. You can sharply take the 5 point parabolas' and add them together. But now Mr camera shaker let in 3d light.

Asenstiven Odin Other : Krishna Mohan Krishna Mohan 1 месяц назад (изменено) Хорошо. Время прекратить покупать 1000 $ телефонов. Спасибо AI. Просто не убивай меня в будущем

Frane Šustić : Amazing stuff, and what is this slower, superior technique called? Just wondering what quality is possible at this point.

David Saintloth : Great find, I hadn't come across this paper yet. Tangent, I'm finding it more difficult to properly categorize my papers as the dividing line between pure ML and the actual practical deployments are getting blurrier. In the last few years I've downloaded papers from architecture to computer graphics...from graphic design to genetics that all use ML in some way. For now rather than place those papers in my big and growing ML sub folder they are going to their source discipline folders. This paper though goes into the ML sub folder as the "Computer graphics" folder isn't quite what super resolution is about (though I've seen a few papers at Siigraph just this year that used ML to dramatically reduce render time for real time rendering of frames by using super resolution approaches as a progressive refinement step). What a great time to be a Engineer-Researcher and alive!!

Asenstiven Odin Other : kastakan kastakan 1 месяц назад Наконец, мы будем иметь возможность смотреть японское порно! : D

cr9pr3 : Imagine using this on textures for realtime 3D Applications. I picture somewhat slowly updating light probed cubemaps. Lower the cubemap res and ENHANCE! Or VR: maybe render like we do now and apply to the section the fovea is concentrated on. Ofcourse its only viable in any way if we still get like another 10-100x speedup.