AI RESEARCH
ProGIC: Progressive and Lightweight Generative Image Compression with Residual Vector Quantization
arXiv CS.CV
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ArXi:2603.02897v2 Announce Type: replace Recent advances in generative image compression (GIC) have delivered remarkable improvements in perceptual quality. However, many GICs rely on large-scale and rigid models, which severely constrain their utility for flexible transmission and practical deployment in low-bitrate scenarios. To address these issues, we propose Progressive Generative Image Compression (ProGIC), a compact codec built on residual vector quantization (RVQ). In RVQ, a sequence of vector quantizers encodes the residuals stage by stage, each with its own codebook.