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This shouldn't be news. Most computer vision NNs are CNNs where the convolutions are basically translating the image into small "textures". "AI sees textures" y
by personjerry 7y ago
This shouldn't be news. Most computer vision NNs are CNNs where the convolutions are basically translating the image into small "textures". "AI sees textures" yeah because that's how we present data to it!
- hammock 7y agoI wonder what would happen if we fed it SVGs instead of JPGs. (Shape files)
- tastroder 7y agoAt that point it's less a task in the context of image processing and more one of graph learning / language processing, depending on how you want to formulate it.
- wongarsu 7y agoHuman vision certainly contains a component where we do 3d reconstruction and adjust our perception based on that. Many optical illusions depend on this step. If we want more human like machine vision then having passes in image processing that deal with more abstract data sounds like a great idea
- mirekrusin 7y agoI don't think those networks can work with variable inputs, they use fixed size images, svg describes paths that highly vary.
- abrichr 7y agoThat's true for convolutional networks. However, recurrent architectures aren't similarly limited, e.g SketchRNN: https://github.com/tensorflow/magenta/blob/master/magenta/models/sketch_rnn/README.md https://github.com/tensorflow/magenta/blob/master/magenta/mo...