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arXiv Computer Vision By Shaohua Pan, Xiao Liu

AV-FlowEdit: Training-Free Prompt-Driven Audio-Visual Editing with Event-Aware Spectral Trajectory Preservation

Read the original on arXiv Computer Vision →

AV-FlowEdit is a training‑free, inversion‑free framework that enables prompt‑driven audio‑visual editing using joint audio‑video diffusion models. It leverages source‑to‑target flow differences to guide edits while preserving non‑target structure and cross‑modal correspondence. The method includes a Cross‑Modal Event‑Aware Spectral Trajectory Preservation module that suppresses drift by combining flow saliency, aligned audio activity, multiscale low‑frequency displacement, and diffusion‑stage scheduling, achieving strong prompt alignment, temporal consistency, and competitive audio quality.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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