Deep Residual Learning in the JPEG Transform Domain

ICCV 2019 Max EhrlichLarry Davis

We introduce a general method of performing Residual Network inference and learning in the JPEG transform domain that allows the network to consume compressed images as input. Our formulation leverages the linearity of the JPEG transform to redefine convolution and batch normalization with a tune-able numerical approximation for ReLu... (read more)

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