Opinion about implementation feasibility (Patch Match algorithm)

Hello guys!

I am thinking to create the Patch Match algorithm using Pytorch. The idea behind the implementation is to use Tensors with GPU support in order to do the calculations fast. A fast overview of patch match algorithm is the following:
Patch match is a randomized algorithm that tries to approximate nearest neighbors of a reference patch in a target set of patches. Here is a video explanation: https://www.youtube.com/watch?v=fMe19oTz6vk (4 min)

Do you think that a Pytorch implementation will be feasible? Also, this algorithm make heavy use of indices so I am not sure if the end result will be fast.

Best regards,

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Hello Filippos,

it would sound like it is feasible (note that there also is a PatchMatch wikipedia page). A month ago, Francisco Massa suggested a possible approach for implementation that should be relatively easy to follow:

Of course, we’d love to see your implementation once it is done. :slight_smile:

Best regards


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