Supplementary materials - STB-VMM: Swin Transformer Based Video Motion Magnification

Published: 24 July 2023| Version 2 | DOI: 10.17632/76s26nrcpv.2
Contributors:
Ricard Lado-Roigé, Marco A. Pérez

Description

Reference benchmark videos showcased in STB-VMM: Swin Transformer Based Video Motion Magnification. This dataset contains the original benchmarks as well as the results obtained using STB-VMM and learning-based video motion magnification (LB-VMM) [10.48550/arXiv.1804.02684]. These videos serve as a qualitative comparison between both learning based methods' image quality. The dataset is intended to help researchers and practitioners in the field of video motion magnification to evaluate and compare the performance of different methods. The code for STB-VMM is open source and available at: https://github.com/RLado/STB-VMM

Files

Steps to reproduce

The code for STB-VMM is open source and available at: https://github.com/RLado/STB-VMM

Institutions

Universitat Ramon Llull, Institut Quimic de Sarria

Categories

Mechanics, Machine Learning, Video, Vibration Testing, Structural Health Monitoring, Experimental Mechanics, Deep Learning

Licence