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BooM-VVT: Boosting Mask-Free Video Virtual Try-On with Image-Level Pseudo Data

Paper recorded by Signals 4 on 2026-09-03 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-03 on arXiv · recorded by Signals 4 on 2026-09-04

Category: cs.CV · 计算机视觉 · first seen 2026-09-04

Abstract

Video virtual try-on (VVT) aims to generate realistic videos of a person wearing a target garment. Recent methods leverage a keyframe-driven video generation paradigm to improve in-the-wild performance, yet they still rely on masks to localize try-on regions, making them vulnerable to large motions and severe occlusions. Although mask-free image-based try-on methods have shown promising results by

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#150 most recent of 237 cs.CV papers we have recorded · ↑ newer: Beyond Retrieval: Progressive Latent Memory Evolution for Streaming Vi · ↓ older: The Shape of Time: Video-Token Contrast for Temporal Understanding in
Cite this page: BooM-VVT: Boosting Mask-Free Video Virtual Try-On with Image-Level Pseudo Data: the #150 most recent of 237 cs.CV papers we have recorded (as of 2026-09-03). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/boom-vvt-boosting-mask-free-video-virtual-try-on-with-image-level-pseudo-data.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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