Colorizing black and white photos with deep learning
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Colorizing black and white photos with deep learning
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Re: Colorizing black and white photos with deep learning
#2The averaging problem in colorization is interesting. If it learns that an apple can be red, green and even yellow - how does it know how to color it?
A HN user in an earlier thread suggested to use a fake/real colorization classifiers as a loss function. [1] But I still feel that it would not solve the averaging problem. It would hop between different colors and probably converge to brown. I haven’t come across a plausible solution so far. [1] https://news.ycombinator.com/item?id=10864801
Re: Colorizing black and white photos with deep learning
#3This is refreshing. I’ve been learning machine learning through Kaggle. Recently and I’m a bit tired with the “tuning hyperparameter” culture. It rewards people that have the pockets to spend on computing power and the time to try every parameter. I’m starting to find problems that don’t have a simple accuracy metric more interesting. It forces me to understand the problem and think in new ways, instead of going down a checklist of optimizations.
Re: Colorizing black and white photos with deep learning
#4The averaging problem in colorization is interesting. If it learns that an apple can be red, green and even yellow - how does it know how to color it? A HN user in an earlier thread suggested to use a fake/real colorization classifiers as a loss function. [1] But I still feel that it would not solve the averaging problem. It would hop between different colors and probably converge to brown. I haven’t come across a pl…
It could try to classify the apple tree or the context, but it would require a lot of training data. If it's out of context, it should select a color based on probability. But it's hard to solve this with just input and output data. The simple solution is to use noncontradictory training data, i.e. only having green apples.
I have an urge to teach it simple logic. Instead of making it brown, it selects the color with the highest probability from a range of colors. However, I haven't come across a deep learning implementation like this to mimic.
Re: Colorizing black and white photos with deep learning
#5Interesting! If nowadays, pictures are colorized by hand in photoshop, it wouldn't be practical to colorize a full black and white movie. I guess this deep learning approach would solve this problem and colorize old black and white classic movies.
Re: Colorizing black and white photos with deep learning
#6Interesting! If nowadays, pictures are colorized by hand in photoshop, it wouldn't be practical to colorize a full black and white movie. I guess this deep learning approach would solve this problem and colorize old black and white classic movies.
I think colorising b&w movies must already be fairly practical given the size of this list:
https://en.wikipedia.org/wiki/List_of_black-and-white_films_...
Re: Colorizing black and white photos with deep learning
#7This is refreshing. I’ve been learning machine learning through Kaggle. Recently and I’m a bit tired with the “tuning hyperparameter” culture. It rewards people that have the pockets to spend on computing power and the time to try every parameter. I’m starting to find problems that don’t have a simple accuracy metric more interesting. It forces me to understand the problem and think in new ways, instead of going down…
Ha, it reminds me of what Andrej Karpathy said "Kaggle competitions need some kind of complexity/compute penalty. I imagine I must be at least the millionth person who has said this." It would be interesting to collaborate/compete on more creative tasks and have different metrics for success.
Re: Colorizing black and white photos with deep learning
#8This is refreshing. I’ve been learning machine learning through Kaggle. Recently and I’m a bit tired with the “tuning hyperparameter” culture. It rewards people that have the pockets to spend on computing power and the time to try every parameter. I’m starting to find problems that don’t have a simple accuracy metric more interesting. It forces me to understand the problem and think in new ways, instead of going down…
I'm also starting to follow people and communities that work with deep learning in new ways. Here are some of my favorites:
Re: Colorizing black and white photos with deep learning
#9Interesting! If nowadays, pictures are colorized by hand in photoshop, it wouldn't be practical to colorize a full black and white movie. I guess this deep learning approach would solve this problem and colorize old black and white classic movies.
Agreed. I imagine this has applications in compression as well. You could stream a movie (or a football game) in black and white and enable each device to color it on the spot. A similar technique could also be done for HD/3D/VR.
Re: Colorizing black and white photos with deep learning
#10This is refreshing. I’ve been learning machine learning through Kaggle. Recently and I’m a bit tired with the “tuning hyperparameter” culture. It rewards people that have the pockets to spend on computing power and the time to try every parameter. I’m starting to find problems that don’t have a simple accuracy metric more interesting. It forces me to understand the problem and think in new ways, instead of going down…
Ha, it reminds me of what Andrej Karpathy said "Kaggle competitions need some kind of complexity/compute penalty. I imagine I must be at least the millionth person who has said this." It would be interesting to collaborate/compete on more creative tasks and have different metrics for success. [1] https://twitter.com/karpathy/status/913619934575390720
So true. Another reason to put constraints in Kaggle competition is due to production environment. How many winner models have been used in production? I suspect this number is near zero. High accuracy with a delayed time makes a ML/DL artefact not usable in production, because from users point of view speed is much more valuable than the difference between 97% and 98% in accuracy.