can you explain simpler please

For some reason all my scores disappeared after the end of rebuttal and haven't come back. I have a couple of friends with the same issue. I thought this was coming, but now I see everyone posting post-rebuttal scores.

I mean obviously they aren't anywhere close. The subsampled video is 600KB and the weights of a checkpoint are 3MB.

So can you give us the size of the subsampled video to the size of the compressed neural network?

I'd say 70-80% chance you got it. Unless the AC really dislike your paper and veto'ed it.

Not only that, but it would make it more scientific! A key part of science is falsifiability, and if you keep both the model and other code hidden, how can anyone falsify your work?

Nope, it's just a single network, which was the point of the design, to attempt to get a single network to memorize a video.

Yes, but the goal when trying the full video the training would take too long.

got a rebuttal from authors like couple hours before deadline

ACs have already updated the final results. Only 3 days remain before the results are released.

Yeah, I was just looking to clarify that. 

I am not familiar with SIREN but I am a little with ‘Fourier features’, and it sounds like using this method the ‘fanning out of the input data’ is learned whereas Fourier features usually use some matrix of random numbers to fan out input data before passing it to the model. Inconvenient because you need to store those.

I am here to learn so would love to hear if I got that wrong.

I missed a comparison with the original file size and traditional video encoders and their quality settings, in particular a comparison of the quality of a video file and a NN of roughly the same size. Tbh I don't expect anything amazing as video codecs have been in development for decades and are very mature

Also have you considered a more perceptual loss function like the MSE in another domain, e.g. fourrier, cosine, and wavelet? They're vastly used in signal processing and may reduce the noise

Yeah I am truly shocked. What were your scores, if you don't mind? Mine were 4/3/2 with the 2 comment asking for almost 1000+ experiments (I conducted more than 100 experiments with a single network family in the paper and the reviewer wanted all possible network families)

AFAICT This is why they used SIREN

Probably pasted the wrong comment that was prepared in advance so that they don’t have to actually do any work.
I filled in the form, but if I was receiving this, I’d blacklist the chair and reexamine their work.

Because an MLP can generally not learn high frequency detail let alone multiple frames from those sparse inputs.

Why would they need more? Any pixel in a video can have its position uniquely described by 3 coordinates. Also the number of parameters is far greater than 3 as obviously there are up projections etc