Suzhi Bi — accepted AI-conference papers

2026

Training-Free Rate-Distortion-Perception Traversal With Diffusion

Yuhan Wang, Suzhi Bi, Angela Yingjun Zhang

ICML 2026poster

The rate-distortion-perception (RDP) tradeoff characterizes the fundamental limits of lossy compression by jointly considering bitrate, reconstruction fidelity, and perceptual quality. While recent neural compression methods have improved perceptual performance, they typically operate at fixed point…

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2025

Traversing Distortion-Perception Tradeoff using a Single Score-Based Generative Model

Yuhan Wang, Suzhi Bi, Ying-Jun Angela Zhang, Xiaojun Yuan

CVPR 2025poster

The distortion-perception (DP) tradeoff reveals a fundamental conflict between distortion metrics (e.g., MSE and PSNR) and perceptual quality. Recent research has increasingly concentrated on evaluating denoising algorithms within the DP framework. However, existing algorithms either prioritize perc…

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