Impressive of the American news channel, CNN, to convert images in minus one second.
Seriously, what/who's CNN here?
Convolutional neural network
Learning to See in the Dark (2018)
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Re: Learning to See in the Dark (2018)
#12Re: Learning to See in the Dark (2018)
#13Impressive of the American news channel, CNN, to convert images in minus one second.
Seriously, what/who's CNN here?
Convolutional Neural Network (for example, some more info here: https://adeshpande3.github.io/A-Beginner%27s-Guide-To-Unders...)
Re: Learning to See in the Dark (2018)
#14Impressive of the American news channel, CNN, to convert images in minus one second.
CNN here is a "Convolutional Neural Network"
Re: Learning to See in the Dark (2018)
#15I was just wondering a couple days ago why the image from my phone is so grainy, while my eyes+brain can see everything clear in the dark (it wasn't completely dark, of course). This seems to replicate the post-processing we do in our brain (which is also a giant neural network). I wonder if the process is similar?
Very small numbers of photons (1) are required to trigger rhodopsin cycle. So primary receptor itself is very very VERY sensitive.
Re: Learning to See in the Dark (2018)
#16It's surprising how little code [1] is needed to do this. On the other hand I feel this is quite dependent on the specific camera models and might not work on the RAW data downloaded from my phone. Happy to be corrected.
[1] - https://github.com/cchen156/Learning-to-See-in-the-Dark/blob...
Re: Learning to See in the Dark (2018)
#17What camera are they shooting at 409,600 ISO at?
Re: Learning to See in the Dark (2018)
#18As a photographer, the comparison to "raw" results without color balance or noise removal seems somewhat deceptive. The effects visible in the video seem easy to quickly replicate with existing techniques, such as the "surface blur" filter that averages out pixel values in areas with similar color.
This happens at the expense of detail in low-contrast areas, producing a plastic-like appearance of human skin and hair, and making low-contrast text unintelligible, which is why it's generally not done by default.
Re: Learning to See in the Dark (2018)
#19It's surprising how little code [1] is needed to do this. On the other hand I feel this is quite dependent on the specific camera models and might not work on the RAW data downloaded from my phone. Happy to be corrected. [1] - https://github.com/cchen156/Learning-to-See-in-the-Dark/blob...
It's a huge amount of code, hidden behind the tensorflow import statements. It's common to credit GPUs for the rapid spread of deep learning, but good GPUs were available for quite a few years before deep learning really took off. As someone who wrote * a lot* of OpenCL code, including my own python wrappers, I'm fairly certain this code would be thousands of lines without a computation graph framework library. These frameworks are really amazing pieces of software engineering and deserve some non-trivial fraction of the credit for the rise of deep learning.
If you want to know what the next hot thing in software engineering will be, just pay attention to whatever Jeff Dean is doing.
Re: Learning to See in the Dark (2018)
#20I believe this should have a (2018) tag.