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Qifan Li

4 accepted papers

2026

Taming Sampling Perturbations with Variance Expansion Loss for Latent Diffusion Models

CVPR 2026

Latent diffusion models have emerged as the dominant framework for high-fidelity and efficient image generation, owing to their ability to learn diffusion processes in compact latent spaces. However, while previous research has focused primarily on reconstruction accuracy and semantic alignment of t

Cited by 0SourcecodeScholar
2026

Texture Vector-Quantization and Reconstruction Aware Prediction for Generative Super-Resolution

ICLR 2026poster

Vector-quantized based models have recently demonstrated strong potential for visual prior modeling. However, existing VQ-based methods simply encode visual features with nearest codebook items and train index predictor with code-level supervision. Due to the richness of visual signal, VQ encoding o…

Cited by 0SourceScholar