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eess.IV2026
End-to-End Learned Image Coding: From Rate-Distortion Optimization to Practical Deployment
Ming Lu, Junqi Shi, Zhan Ma
End-to-end learned image coding (LIC) has achieved substantial improvements in rate--distortion (R--D) performance, yet practical deployment requires addressing a broader set of sy…
eess.IV2026
Hadamard-Domain Model Quantization for Learned Image Coding
Junqi Shi, Chongzhi Wang, Yiwen He +2
Uniform INT8 quantization is attractive for deploying learned image coding (LIC), but its rate--distortion (R--D) performance is often limited by heavy-tailed tensors and large int…
eess.IV2026
DiT-IC: Aligned Diffusion Transformer for Efficient Image Compression
Junqi Shi, Ming Lu, Xingchen Li +3
Diffusion-based image compression has recently shown outstanding perceptual fidelity, yet its practicality is hindered by prohibitive sampling overhead and high memory usage. Most…