ProGIC applies residual vector quantization with a lightweight CNN-attention backbone to deliver progressive generative image compression with claimed perceptual gains and over 10x faster encoding/decoding versus MS-ILLM.
Misc: Ultra-low bitrate image semantic compres- sion driven by large multimodal model.IEEE Transactions on Image Processing, 34:335–349
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ProGIC: Progressive and Lightweight Generative Image Compression with Residual Vector Quantization
ProGIC applies residual vector quantization with a lightweight CNN-attention backbone to deliver progressive generative image compression with claimed perceptual gains and over 10x faster encoding/decoding versus MS-ILLM.