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Learned visual compression is an important and active task in multimedia.
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End-to-end optimized image compression
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Joint autoregressive and hierarchical priors for learned image compression
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Scale-space flow for end-to-end optimized video compression
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Learned image compression with discretized gaussian mixture likelihoods and attention modules
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An image is worth 16x16 words: Transformers for image recognition at scale
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Lossy image compression with quantized hierarchical vaes
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Learned image compression with gaussian-laplacian-logistic mixture model and concatenated residual modules
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Long range language modeling via gated state spaces
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