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License: MIT License
a Pytorch library for multi-view 3D understanding and generation
License: MIT License
we need to create a benchmarking table as we discussed earlier that compares speed, cost, and performance of different submodules , and also reproduce results of other works ( eg. classification with MVCNN, segmentation , nerfs , etc ) and report the performance of those others works using MVtorch ( please see again the Pytorch3d arxive paper )
multi-view stereo example is necessary since its one of the oldest tasks on multi-view ( I recommend taking this modern example from CVPR 2022 and try to do it in MVtorch , its using Pytorch3d so it should be straightforward ) . please watch this video to know what they are doing in this MVS paper.
Please write down instructions to anyone who wants to add and contribute to the library ( see pytorch3D ) so they can fork and pull requests and then we would need to approve and merge to the main branch
[EXAMPLE] Structure-from-motion is also one of the most important multi-view applications, typically using colormap. this ICCV21 paper is a good starting point ( maybe we can do something with MVtorch there when camera poses are available)
creating posed multi-view datasets using MVtorch rendering , 3D dataset , and saving camera parameters and rendered images.
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