STB-VMM: Swin Transformer based Video Motion Magnification

Ricard Lado-Roigé, Marco A. Pérez

Producció científica: Article en revista indexadaArticleAvaluat per experts

3 Cites (Scopus)


The goal of video motion magnification techniques is to magnify small motions in a video to reveal previously invisible or unseen movement. Its uses extend from bio-medical applications and deepfake detection to structural modal analysis and predictive maintenance. However, discerning small motion from noise is a complex task, especially when attempting to magnify very subtle, often sub-pixel movement. As a result, motion magnification techniques generally suffer from noisy and blurry outputs. This work presents a new state-of-the-art model based on the Swin Transformer, which offers better tolerance to noisy inputs as well as higher-quality outputs that exhibit less noise, blurriness, and artifacts than prior-art. Improvements in output image quality will enable more precise measurements for any application reliant on magnified video sequences, and may enable further development of video motion magnification techniques in new technical fields.

Idioma originalAnglès
Número d’article110493
Nombre de pàgines10
RevistaKnowledge-Based Systems
Estat de la publicacióPublicada - 7 de juny 2023


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