AI RESEARCH
DMAligner: Enhancing Image Alignment via Diffusion Model Based View Synthesis
arXiv CS.CV
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ArXi:2602.23022v2 Announce Type: replace Image alignment is a fundamental task in computer vision with broad applications. Existing methods predominantly employ optical flow-based image warping. However, this technique is susceptible to common challenges such as occlusions and illumination variations, leading to degraded alignment visual quality and compromised accuracy in downstream tasks. In this paper, we present DMAligner, a diffusion-based framework for image alignment through alignment-oriented view synthesis.