4 papers
Gen2-IC: Bridging Generative Models and Image Codecs through Latent Transport
Yinhuan Huang, Hao Cao, Pu chen +3
Diffusion-based image compression has achieved strong perceptual quality at ultra-low bitrates. However, existing codecs are often tied to specific backbones and specialized compon…
ContextCodec: Content-Focused Context Guidance for Ultra-Low Bitrate Speech Coding
Chengbin Liang, Wenqi Guo, Hao Cao +1
Neural speech codecs enable low-bitrate speech communication, yet at ultra-low bitrates (< 1000 bps) preserving perceptual quality and intelligibility is challenging. Existing desi…
Efficient Learned Image Compression without Entropy Coding
Hao Cao, Wenqi Guo, Zhijin Qin +1
Entropy coding is widely used in typical learned image compression (LIC) that converts latents into a compact bitstream. However, entropy coding is typically sequential and becomes…
ProGIC: Progressive and Lightweight Generative Image Compression with Residual Vector Quantization
Hao Cao, Chengbin Liang, Wenqi Guo +2
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 s…