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LVQAC: Lattice Vector Quantization Coupled With Spatially Adaptive Companding for Efficient Learned Image Compression

CVPR 2023 · Architectures and efficiency › Quantization · approach: Post-training weight quantization · 25 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace scalar quantization with LVQACCheng2020 with autoregressive context · KodakBD-Rate: 3.35 -> 3.12Helped
Replace scalar quantization with LVQACCheng2020 with checkerboard context · KodakBD-Rate: 3.89 -> 3.39Helped
Replace scalar quantization with LVQACMinnen2018 with autoregressive context · KodakBD-Rate: 14.92 -> 14.75Helped
Replace scalar quantization with LVQACMinnen2018 with checkerboard context · KodakBD-Rate: 20.00 -> 16.17Helped
Add spatially adaptive companding to LVQ (ablation)Cheng2020 with autoregressive context · KodakBD-Rate: 3.24 -> 3.12Helped
Add LVQ to scalar quantization with AC (ablation)Cheng2020 with autoregressive context · KodakBD-Rate: 3.30 -> 3.12Helped
Add spatially adaptive companding to LVQ (ablation)Cheng2020 with checkerboard context · KodakBD-Rate: 3.68 -> 3.39Helped
Add LVQ to scalar quantization with AC (ablation)Cheng2020 with checkerboard context · KodakBD-Rate: 3.82 -> 3.39Helped
Add spatially adaptive companding to LVQ (ablation)Minnen2018 with autoregressive context · KodakBD-Rate: 14.86 -> 14.75Helped
Add LVQ to scalar quantization with AC (ablation)Minnen2018 with autoregressive context · KodakBD-Rate: 14.88 -> 14.75Helped
Add spatially adaptive companding to LVQ (ablation)Minnen2018 with checkerboard context · KodakBD-Rate: 18.43 -> 16.17Helped
Add LVQ to scalar quantization with AC (ablation)Minnen2018 with checkerboard context · KodakBD-Rate: 19.29 -> 16.17Helped

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