A rate-distortion-aware neural architecture search plus joint pruning and 8-bit quantization reduces learned image compression model size by up to about 4.9x with small rate-distortion penalty.
Next, we demon- strate our proposed NAS procedure for determining the layer- wise pruning ratio of the pruned model
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Structured Pruning and Quantization for Learned Image Compression
A rate-distortion-aware neural architecture search plus joint pruning and 8-bit quantization reduces learned image compression model size by up to about 4.9x with small rate-distortion penalty.