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Generative model based image lossless compression algorithms have seen agreat success in improving compression ratio. However, the throughput for mostof them is less than 1 MB/s even with the most advanced AI accelerated chips,preventing them from most real-world applications, which often require 100MB/s. In this paper, we propose PILC, an end-to-end image lossless compressionframework that achieves 200 MB/s for both compression and decompression with asingle NVIDIA Tesla V100 GPU, 10 times faster than the most efficient onebefore. To obtain this result, we first develop an AI codec that combinesauto-regressive model and VQ-VAE which performs well in lightweight setting,then we design a low complexity entropy coder that works well with our codec.Experiments show that our framework compresses better than PNG by a margin of30% in multiple datasets. We believe this is an important step to bring AIcompression forward to commercial use.

PILC: Practical Image Lossless Compression with an End-to-end GPU Oriented Neural Framework