Seems like a slightly unfair comparison. Training the compressor moves data from the images into the compressor, making the bit per pixel evaluation slightly more iffy.
As long as they don't test on the training set it's a fair comparison isn't it?
Real-Time Adaptive Image Compression
31–40 of 51 posts
Re: Real-Time Adaptive Image Compression
#32[deleted]
Re: Real-Time Adaptive Image Compression
#33Very impressive work, though it seems like a mistake to focus on compression, which gets less valuable as storage and bandwidth gets cheaper. You need only look to the staying power of jpeg, which is so far from the state of the art, yet it's not going anywhere. Why? The demand for replacing it is not strong enough. They obviously have some good image priors here, if I were them I would consider applying this tech to…
It isn't 'very impressive work', it is marketing for Silicon Valley (impressive marketing though). Literally the first sentence of the linked page: "Even though over 70% of internet traffic today is digital media, the way images and video are represented and transmitted has not evolved much in the past 20 years (apart from Pied Piper's Middle-Out algorithm)." EDIT: This is embarrassing that not one person in this thr…
There are real people behind it:
https://scholar.google.ca/citations?user=reEAEWsAAAAJ&hl=en
https://scholar.google.ca/citations?user=OXFjRnEAAAAJ&hl=en
Company entry on Linkedin: https://www.linkedin.com/company-beta/12953035/
Re: Real-Time Adaptive Image Compression
#34I wonder how this compares to FLIF. I also tried to compress images based on shape and structure but by approximating these using skeletons. I'm just a bit struggling with their performance comparison. The graphs they present are very pretty and promising but for the presented images we're quite left in the dark. They dump some images and theirs looks prettier and the authors give us some indication of quality but it…
FLIF is lossless. So very very different.
Err... FLIF is intended for lossless compression, but can be lossy (it doesn't perform as well as intentionally lossy codecs, although that might also be a matter of optimising for it).
However, it also has a kind of adaptive ML-ish approach so it might be technically similar.
> FLIF is based on MANIAC compression. MANIAC (Meta-Adaptive Near-zero Integer Arithmetic Coding) is an algorithm for entropy coding developed by Jon Sneyers and Pieter Wuille. It is a variant of CABAC (context-adaptive binary arithmetic coding), where instead of using a multi-dimensional array of quantized local image information, the contexts are nodes of decision trees which are dynamically learned at encode time. This means a much more image-specific context model can be used, resulting in better compression.
Re: Real-Time Adaptive Image Compression
#35From their website: > Lubomir holds a Ph.D. from UC Berkeley, 20 years of professional experience, 50+ issued patents and 5000+ citations. I just hope this type of research isn't going to end in a patent encumbrance, like it did with JPEG and MPEG. These techniques are right around the corner, no matter who invents the file formats. So if their idea is to lock these general ideas down with more patents, I'd want them…
They are going to capitalize on it, make no mistake.
Re: Real-Time Adaptive Image Compression
#36Earlier quoted context omitted.
Not really. As long as the decompressor needs just an image file and no other data, it's a fair game.
How large is the decompressor to download? Is this image compression tool good at images it was not trained on? How bad does it get in those situations? Is this training data fixed into the codex forever? Will there be slightly different image codexs that have different training data? That would be sort of hellish.
You'd need some bits in the file telling you which trained decoder you need to get the proper image out.
What would the image of that girl look like if they used WaveOne Aerial?
How is this not cheating if the example image they used to compare algorithms is in the training data?
Re: Real-Time Adaptive Image Compression
#37Earlier quoted context omitted.
It isn't 'very impressive work', it is marketing for Silicon Valley (impressive marketing though). Literally the first sentence of the linked page: "Even though over 70% of internet traffic today is digital media, the way images and video are represented and transmitted has not evolved much in the past 20 years (apart from Pied Piper's Middle-Out algorithm)." EDIT: This is embarrassing that not one person in this thr…
There are real people behind it: https://scholar.google.ca/citations?user=reEAEWsAAAAJ&hl=en https://scholar.google.ca/citations?user=OXFjRnEAAAAJ&hl=en Company entry on Linkedin: https://www.linkedin.com/company-beta/12953035/
It literally quotes a fictional TV show in the synopsis and directly in the paper. Are you seriously not getting that is is fiction?
Why would they have this in the actual PDF?
"Finally, Pied Piper has recently claimed to employ ML techniques in its Middle-Out algorithm (Judge et al., 2016), although their nature is shrouded in mystery"
This is promotion, they are getting a fake paper to permeate throughout the internet. If I had to guess, I would say they are making a statement about reproducing results in academia and not taking a single paper as gospel. If so, I think they are making their point pretty well.
Re: Real-Time Adaptive Image Compression
#38From their website: > Lubomir holds a Ph.D. from UC Berkeley, 20 years of professional experience, 50+ issued patents and 5000+ citations. I just hope this type of research isn't going to end in a patent encumbrance, like it did with JPEG and MPEG. These techniques are right around the corner, no matter who invents the file formats. So if their idea is to lock these general ideas down with more patents, I'd want them…
This also looks like a meta-algorithm, an algorithmic way to generate domain specific compressors, potentially anything this thing creates would also be covered by patents.
Re: Real-Time Adaptive Image Compression
#39A rarely discussed danger of all machine learning models: If they don't know the answer, they'll rather make something up.
Here's a Google Translate example: https://twitter.com/keff85/status/862690920805916672
I wouldn't like to lose a part of parcel in a lawsuit because an adaptive algorithm made up some details in aerial photograph so that it compresses better ...
Re: Real-Time Adaptive Image Compression
#40Earlier quoted context omitted.
There are real people behind it: https://scholar.google.ca/citations?user=reEAEWsAAAAJ&hl=en https://scholar.google.ca/citations?user=OXFjRnEAAAAJ&hl=en Company entry on Linkedin: https://www.linkedin.com/company-beta/12953035/
It literally quotes a fictional TV show in the synopsis and directly in the paper. Are you seriously not getting that is is fiction? Why would they have this in the actual PDF? "Finally, Pied Piper has recently claimed to employ ML techniques in its Middle-Out algorithm (Judge et al., 2016), although their nature is shrouded in mystery" This is promotion, they are getting a fake paper to permeate throughout the inter…
Okay, it may be. It is something that can be done from a technical level for sure, given enough training data and enough data on the client side to do reconstructions.
I guess once you get popular enough you can get TV consultants who can propose real solutions as TV props. Heh.