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Translating and implementing L2 Scale Invariant Loss from research to code. Exploring the equation as a simple program using numpy, then adding in optimization methods. Core functionality will showcase disparity loss as python code using Numpy, CUDA programming and PyTorch.

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danieaneta/L2_Scale_Invariant_Loss

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Implementing L2 Scale Invariant Loss as a simple algorithm.

Papers: https://arxiv.org/pdf/1406.2283 "Depth Map Prediction from a Single Image using a Multi-Scale Deep Network" https://arxiv.org/pdf/1411.4734 "Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture"

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Translating and implementing L2 Scale Invariant Loss from research to code. Exploring the equation as a simple program using numpy, then adding in optimization methods. Core functionality will showcase disparity loss as python code using Numpy, CUDA programming and PyTorch.

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