Showing 2 open source projects for "vector quantization"

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    NÜWA - Pytorch

    NÜWA - Pytorch

    Implementation of NÜWA, attention network for text to video synthesis

    Implementation of NÜWA, state of the art attention network for text-to-video synthesis, in Pytorch. It also contains an extension into video and audio generation, using a dual decoder approach. It seems as though a diffusion-based method has taken the new throne for SOTA. However, I will continue on with NUWA, extending it to use multi-headed codes + hierarchical causal transformer. I think that direction is untapped for improving on this line of work. In the paper, they also present a way...
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  • 2
    RQ-Transformer

    RQ-Transformer

    Implementation of RQ Transformer, autoregressive image generation

    ...For autoregressive (AR) modeling of high-resolution images, vector quantization (VQ) represents an image as a sequence of discrete codes. A short sequence length is important for an AR model to reduce its computational costs to consider long-range interactions of codes. However, we postulate that previous VQ cannot shorten the code sequence and generate high-fidelity images together in terms of the rate-distortion trade-off.
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