Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).
Abstract: Conventional semantic communication systems require training task-specific semantic encoders on each user device and corresponding decoders on the server for every client, resulting in ...
A recent publication from IMDEA Materials Institute and the Technical University of Madrid (UPM) presents a major step ...
TAEHV is a Tiny AutoEncoder for Hunyuan Video (and other similar video models). TAEHV can encode and decode latents into videos more cheaply (in time & memory) than the full-size video VAEs, at the ...
Abstract: The existing deep learning based reversible data hiding (RDH) predictors typically adopt standard convolutions for extracting features, which inherently fails to capture contextual ...
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