Top Tweets for #NeuralPatches
Earlier with @ngutten we realized how similar capsule networks are to #NeuralPatches (I'm a big fan), except for recognition rather than generation.
Tricky part with #NeuralPatches is always tweaking and tuning the parameters, even if it's "automatically" creating the soft masks...
Photo-realistic Facial Texture Transfer https://t.co/wwugVibip1 Uses #NeuralPatches again w/ extra pre-processing & custom losses. #ML #AI
@YS I tried many criteria, paper suggests "mean squared error" (a standard in statistics), #NeuralPatches uses "normalized cross-correlation".
@graphific #NeuralPatches is better here because it leverages rotated patches (15-30-45 degrees). Would be nice to have dis-entagled rotation feature!
13/ #NeuralPatches does brute force coarse-to-fine generation. My `forward` branch uses fast PatchMatch algorithm: https://t.co/xkQldbETgN
10/ Personally I attribute much of this quality to using #NeuralPatches (Li, 2016)βwhich was underrated! The difference is more incremental:
@quasimondo That alone would just be #NeuralPatches. It'll soon cross reference two images being reconstructed at the same time in opposite style.
3/ (β That's the generator.) The discriminator is a patch-based network inspired by fast-#NeuralPatches. https://t.co/zKVJmavX46
Source code for "High-Res Image In-Painting using Multi-Scale #NeuralPatches Synthesis" https://t.co/ZuWdagGku0 in Lua/Torch #DeepLearning
13/ If they had approached this differently, likely they would have just fixed #NeuralPatches variety problem. I'm sure there are many ways!
10/ The only problem with #NeuralPatches is that it lacks variety (top row). I blogged & fixed it here: https://t.co/vbWMjaXBuu
8/ On a higher-level, I think they are too quick at rejecting CNNMRF (a.k.a. #NeuralPatches) as problems pile up later in paper:
25/ I don't have video, so not sure how it looks in motion. It takes 6-8 mins for #NeuralPatches compared to 40 mins reported in paper! π
22/ Took a short break to render quick examples. First is #NeuralDoodle (with mask), then #NeuralPatches (no mask) and finally #NeuralStyle.
19/ Stylized result with plain-old #NeuralStyle retains nothing of this. #NeuralPatches would color within the lines, but wouldn't fix it.
.@DeepForger 17/ So #NeuralPatches would be able to fix these blobs in the images from the paper. But there's another level deeper still...
13/ In practice, it means #NeuralPatches is well suited to painting the impressionist styles they're aiming for. https://t.co/4ORbjNjylB
@EdPlocher Hereβs my #DeepForgery with techniques by Pierre Auguste Renoir from ca. 1892.
https://t.co/YJcFNN1Vaa
11/ At the risk of sounding like a broken record, the solution to this is the 12 month-old #NeuralPatches algorithm! https://t.co/PT6IIbQCvq
[1] π https://t.co/sElUWbN3Gx Photo-realistic style transfer technique by Li & Wand, combines patch-based image processing with convnet.
![alexjc's tweet photo. [1] π https://t.co/sElUWbN3Gx Photo-realistic style transfer technique by Li & Wand, combines patch-based image processing with convnet. https://t.co/g6igWJ4JC8](https://pbs.twimg.com/media/Cza8Zz3XAAAyPI4.jpg)
![alexjc's tweet photo. [1] π https://t.co/sElUWbN3Gx Photo-realistic style transfer technique by Li & Wand, combines patch-based image processing with convnet. https://t.co/g6igWJ4JC8](https://pbs.twimg.com/media/Cza8XOJWQAAWIBX.jpg)
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