A single rate-variable generative compression model treats quantization as a forward corruption and reverses it with a two-step denoiser, outperforming prior generative codecs on perceptual quality benchmarks.
In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (July 2017) 7, 8
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Generative Image Compression by Estimating Gradients of the Rate-variable Feature Distribution
A single rate-variable generative compression model treats quantization as a forward corruption and reverses it with a two-step denoiser, outperforming prior generative codecs on perceptual quality benchmarks.