arXiv Machine Learning
Jun 29

StableMotion: One-Step Motion Estimation with Diffusion Prior

arXiv:2505. 06668v2 Announce Type: replace-cross Abstract: We present StableMotion, a novel framework that leverages geometric and content priors from pretrained large-scale image diffusion models for motion estimation in single-image rectification tasks such as Stitched Image Rectangling (SIR) and Rolling Shutter Correction (RSC).

By Ziyi Wang, Haipeng Li, Lin Sui, Tianhao Zhou, Hai Jiang, Lang Nie, Bing Zeng, Shuaicheng Liu
arXiv Computer Vision
1d ago

Local Epistemic Uncertainty Guided Active Sampling for Plug-and-play Diffusive Image Restoration

The paper introduces LEADer, a framework that uses local epistemic uncertainty to guide active sampling in diffusion-based image restoration. By adjusting prior strength per pixel and pruning sampling trajectories based on uncertainty traces, LEADer balances detail preservation with artifact suppression and accelerates convergence. The method is plug‑and‑play, theoretically guarantees data consistency and stable convergence, and improves performance across multiple state‑of‑the‑art diffusion models with minimal memory overhead.

By Jiaqi Zhang, Zheng Pang, Rongrong Gao, Qiyuan Zhang, Yang Yang