collaborators

5 papers

cs.CV2026

CADC: Content Adaptive Diffusion-Based Generative Image Compression

Xihua Sheng, Lingyu Zhu, Tianyu Zhang +3

Diffusion-based generative image compression has demonstrated remarkable potential for achieving realistic reconstruction at ultra-low bitrates. The key to unlocking this potential…

cs.CV2026

Ultra-Low Bitrate Perceptual Image Compression with Shallow Encoder

Tianyu Zhang, Dong Liu, Chang Wen Chen

Ultra-low bitrate image compression (below 0.05 bits per pixel) is increasingly critical for bandwidth-constrained and computation-limited encoding scenarios such as edge devices.…

cs.CV2025

Latent Posterior-Mean Rectified Flow for Higher-Fidelity Perceptual Face Restoration

Xin Luo, Menglin Zhang, Yunwei Lan +4

The Perception-Distortion tradeoff (PD-tradeoff) theory suggests that face restoration algorithms must balance perceptual quality and fidelity. To achieve minimal distortion while…

eess.IV2025

StableCodec: Taming One-Step Diffusion for Extreme Image Compression

Tianyu Zhang, Xin Luo, Li Li +1

Diffusion-based image compression has shown remarkable potential for achieving ultra-low bitrate coding (less than 0.05 bits per pixel) with high realism, by leveraging the generat…

eess.IV2025

Few-Shot Domain Adaptation for Learned Image Compression

Tianyu Zhang, Haotian Zhang, Yuqi Li +2

Learned image compression (LIC) has achieved state-of-the-art rate-distortion performance, deemed promising for next-generation image compression techniques. However, pre-trained L…