BooM‑VVT is a mask‑free video virtual try‑on framework that builds on a keyframe‑driven paradigm. It introduces a multi‑stage training strategy using image‑level pseudo data to learn mask‑free localization, a garment‑sensitive keyframe sampling method to capture garment appearance, and a Frame‑Shared 3D‑RoPE module to align keyframes with target video frames for accurate garment detail transfer. The authors also release OmniView, a large‑scale multi‑view try‑on dataset, and demonstrate that BooM‑VVT outperforms existing methods in temporal consistency and garment fidelity.
By Wei Zhang, Xin Li, Peishu Shi, Jialin Gao, Xuekang Peng, Zhichao Lian, Yeying Jin
arXiv:2608. 05745v1 Announce Type: cross Abstract: Video Virtual Try-On (VVT) synthesizes a video of a person wearing a target garment while preserving identity, motion, and scene dynamics.
By Yushe Cao, Shikun Feng, Fei Shen, Haikuo Peng, Jianqiang Xia, Yiheng Zhu, Dianxi Shi, Chun Yu
arXiv:2608.30450v1 Announce Type: new
Abstract: Video virtual try-on aims to transfer a target garment onto a moving person across video frames. Current methods rely on human parsing masks or pose ke...
By Shengyao Chen, Xianbing Sun, Liqing Zhang, Jianfu Zhang
OmniShowcase introduces a method for generating omnidirectional videos of a specific subject from a handful of multi‑view images. It combines an automated data‑synthesis pipeline that creates training videos with diverse camera trajectories driven by the subject’s geometry, and a geometry‑conditioning technique that supplies the model with surface‑normal maps reconstructed from the reference views. The authors release Showcase‑4K, a large corpus of 3D‑asset‑based videos with 12 camera motions and 88 trajectory configurations, and ShowcaseBench, a held‑out evaluation set with source meshes and camera parameters.
By Junyeong Ahn, Geonwoo Kim, Kinam Kim, Gihwi Kim, Hoonjin Jung, Hyojin Jang, Jaegul Choo
arXiv:2609.36937v1 Announce Type: cross
Abstract: Human image animation aims to transfer motion from a driving video to subjects in a reference image. Despite remarkable progress in video generation,...
By Sangeyl Lee, Seunghyun Shin, Seungho Park, Wooseok Jeon, Hae-Gon Jeon
arXiv:2610.23856v1 Announce Type: new
Abstract: Generated videos often lose geometric consistency under camera motion: structures warp under viewpoint change, parallax becomes inconsistent, and smoot...
By Weijie Lyu, Tiancheng Shen, Jason Li, Yujing Wang, Xiaoyuan Wang, Haobo Yuan, Yizhou Zhao, Ming-Hsuan Yang