arXiv AI By Yuxuan Chen, Feng Xie, Jiagao Hu, Fuhao Li, Zepeng Wang, Fei Wang, Daiguo Zhou

LociArt: A Unified Paradigm for Free-Style Local Video Stylization

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LociArt introduces a unified framework for free‑style local video stylization, allowing precise specification of where to stylize and which style to apply while preserving non‑target content. The core method, GRNStyle, builds on Generative Refinement Networks and uses a polar style‑aware mask to embed style identities as equal‑norm directions within selected regions. An automated pipeline generates paired supervision, leading to the LociArt‑100K dataset and benchmark, which evaluate regional style quality, non‑target preservation, and temporal consistency, and experiments show GRNStyle outperforms existing methods in these aspects.

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arXiv Computer Vision
Aug 21

ID-V2V: Identity-Preserving Video Restylization

arXiv:2607. 22830v2 Announce Type: replace Abstract: In visual storytelling, human performances are central to creative intent and narrative meaning.

By Yuancheng Xu, Mingming He, Pablo Salamanca, Li Ma, Yash Kant, Emmett Steven, Paul Debevec, Ning Yu
arXiv AI
Oct 9

VINCIE-NExT: Unlocking Video Editing from Images via In-Context Modeling

VINCIE‑NExT is a unified framework that transfers image editing capabilities to video editing by using in‑context visual demonstrations. It decomposes video editing into a chain of sub‑tasks (Video → Image → Image → Video), routing editing intent through the image domain and enabling joint training from heterogeneous image and video data under a single diffusion objective. The method introduces a novel position encoding to link image demonstrations and video frames, allowing pixel‑faithful appearance propagation, and supports test‑time scaling through progressive diffusion stages.

By Leigang Qu, Feng Cheng, Ziyan Yang, Bangbang Yang, Zhaoyang Huang, Wei Chow, Yicong Li, Wenjie Wang, Tat-Seng Chua, Yan Zeng