AI RESEARCH

Preserving Source Video Realism: High-Fidelity Face Swapping for Cinematic Quality

arXiv CS.CV

ArXi:2512.07951v2 Announce Type: replace Video face swapping is crucial in film and entertainment production, where achieving high fidelity and temporal consistency over long and complex video sequences remains a significant challenge. Inspired by recent advances in reference-guided image editing, we explore whether rich visual attributes from source videos can be similarly leveraged to enhance both fidelity and temporal coherence in video face swapping. Building on this insight, this work presents LivingSwap, the first video reference guided face swapping model.