AI RESEARCH

Image-to-Video Diffusion: From Foundations to Open Frontiers

arXiv CS.CV

ArXi:2605.17248v1 Announce Type: new Diffusion-based \textit{image-to-video} (I2V) generation has become a central direction in generative models by turning a reference image, with optional conditions, into a temporally coherent video. Compared with broader video generation settings, this task places stricter demands on content consistency, identity preservation, and motion coherence. Although the literature grows rapidly, existing works mostly discuss I2V generation within broader topics and still lack a dedicated taxonomy together with a systematic analysis centered on this field.