feat(results): add Checkerboard and ELIC papers

[YodaEmbedding]

Official results from Checkerboard and ELIC papers.

Measured using WebPlotDigitizer.

[nessvan]

Are you going to update the result image by adding elic to the graph? Thank you.

[YodaEmbedding]

This is only the paper's reported results -- not the CompressAI implementation. The datasets and chosen GMM $K=3$ may be different from a potential future implementation from CompressAI.

But for reference, here's a plot anyways:

Generated via:

python -m compressai.utils.plot \
    -o kodak-psnr.png \
    --title="Performance evaluation on Kodak - PSNR (RGB)" \
    --axes 0.00 2.25 26 41 \
    -f \
    results/image/kodak/paper-elic2022_mse.json \
    results/image/kodak/vtm.json \
    results/image/kodak/paper-cheng2020-checkerboard-6M_mse.json \
    results/image/kodak/compressai-cheng2020-anchor_mse_cuda.json \
    results/image/kodak/compressai-mbt2018_mse_cuda.json \
    results/image/kodak/av1.json \
    results/image/kodak/compressai-mbt2018-mean_mse_cuda.json \
    results/image/kodak/bpg_444_x265_ycbcr.json \
    results/image/kodak/hm.json \
    results/image/kodak/compressai-bmshj2018-hyperprior_mse_cuda.json \
    results/image/kodak/compressai-bmshj2018-factorized_mse_cuda.json \
    results/image/kodak/webp.json \
    results/image/kodak/jpeg2000.json \
    results/image/kodak/jpeg.json

[YodaEmbedding]

Side note: I wonder if it would have been more consistent naming to call elic2022 one of the following:

• cheng2020-elic (consistent with cheng2020-checkerboard; indicates that the same $g_a, g_s, h_a, h_s$ were used as cheng2020-anchor)
• he2022 (consistent with traditional author-year format; better credits author)
• elic2022 (breaks convention, but more recognizable than "he2022")

Is ELIC the entire model or just the entropy/context model? What would we call it if we applied ELIC's "uneven channel groups + checkerboard" context model to a different set of $g_a, g_s, h_a, h_s$? Questions!