arXiv Computer Vision
Sep 16

MDN-Control: Mask-Depth-Noise Guided Region Control for Multi-Subject Video Editing

MDN-Control is a training‑free framework for multi‑subject video editing that jointly controls target localization, occlusion geometry, and appearance initialization. It uses mask‑guided localization for consistent target placement, depth‑aware occlusion control to resolve boundaries between overlapping subjects, and noise‑latent prompting to retrieve Gaussian initializations from a noise library for prompt‑relevant priors. Experiments on MSVBench show that MDN‑Control achieves the lowest CM‑Err and the highest Q‑Edit while maintaining competitive text alignment and temporal consistency.

By Jiayi Yu, Xi Ye, Lina Wang, Yunkun Xia
Hugging Face Trending Papers
Jul 23

PC-Edit: Prompt-Contrastive Region Discovery and Region-Guided Editing

Replacing an object with one that differs in category or shape requires complete source removal, natural target formation unconstrained by the source silhouette, and preservation of unrelated content. Existing training-free editors either localize edits from terminal predictions under source and target prompts or preserve unrelated content through spatially unselective source-feature reuse without explicit region discovery.