Unmanned vehicles require large amounts of diverse data to train their machine vision modules. Importantly, data should include rare yet important events that the
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MAE, SlimCAE and DANICE: towards practical neural image compression
Neural image and video codecs achieve competitive rate-distortion performance. However, they have a series of practical limitations, such as relying on heavy models, that
Read MoreNeural image compression in a nutshell (part 2: architectures and comparison)
Neural image codecs typically use specific elements in their architectures, such as GDN layers, hyperpriors and autoregressive context models. These elements allow exploiting contextual
Read MoreNeural image compression in a nutshell (part 1: main idea)
Neural image compression (a.k.a. learned image compression) is a new paradigm where codecs are modeled as deep neural networks whose parameters are learned from
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