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DirectSwap: Paired, Mask-Free Video Head Swapping with Full-Reference Evaluation

arxiv.org/abs/2512.09417

Updated 51 min ago · first seen 11 Sept 2026

paper_01M294H32C4NYXYZKJXA6V9NEP

Published
11 Sept 2026
T1 · 51 min ago
arXiv
2512.09417
T1 · 51 min ago
Category
cs.CV
T1 · 51 min ago

Abstract

Head swapping replaces an entire head while preserving pose, expression, body motion, and scene. Progress is limited by the lack of cross-identity paired videos: real footage cannot provide different identities performing exactly the same motion, leaving the task without paired supervision or frame-aligned ground truth. Existing methods therefore rely on same-identity masked reconstruction, which restricts supervision to predefined editable regions. To address this, we introduce an identity-expression decoupled synthesis pipeline that constructs expression-synchronized cross-identity video pairs from real footage. Expression-bearing facial regions are retained under small clip-consistent geometric perturbations, while the surrounding head is regenerated with a new identity as synthesized swapping input. These pairs form a cross-identity benchmark with frame-aligned real-world video as ground-truth targets, enabling full-reference evaluation of identity, expression, pose, reconstruction fidelity, and temporal stability. This yields HeadSwapBench, the first cross-identity paired dataset for video head swapping, supporting both training (20,278 videos) and benchmarking (1,040 videos). With the cross-identity supervision enabled by this paired dataset, we propose DirectSwap, a mask-free video head swapping training paradigm. Under otherwise identical settings, this formulation outperforms head- and rectangle-masked same-identity reconstruction, particularly for bidirectional head-silhouette changes. At inference, driving-output divergence and emergent reference attention estimate the edit support, allowing unchanged non-head content to be restored from the driving video without external segmentation or additional training. On 1,040 clips from 104 unseen subjects, the resulting model demonstrates that the proposed paired supervision supports effective whole-head swapping.

Authors 7

Yanan Wang, Shengcai Liao, Panwen Hu, Xin Li, Fan Yang, Guangxi Liu, Xiaodan Liang

Specification

Official page

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

Arxiv announce type
replace

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

arXiv id
2512.09417

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

Categories
cs.CV

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

PDF

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

Primary category
cs.CV

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

Published
11 Sept 2026

Source:arXiv (Atom API + RSS)T1observed 51 min agohigh

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Provenance

Attributed facts

9

Source tiers

T19

Freshest observation

51 min ago

Conflicts

None