Yihang Bao

LearnIR: Learnable Posterior Sampling for Real-World Image Restoration

Image restoration in real-world conditions is highly challenging due to heterogeneous degradations such as haze, noise, shadows, and blur. Existing diffusion-based methods remain limited: conditional generation struggles to balance fidelity and realism, inversion-based approaches accumulate errors,…