Video conferencing applications play an important role in our day-to-day life. They enable people to meet, work, and collaborate remotely, especially in circumstances where physical meetings are not possible (e.g., pandemic scenarios, long distances, etc.). However, such applications might invade people's privacy, such as disclosing their sensitive information. In this dataset, we recorded different video conferencing with diverse real and virtual backgrounds, changing subjects, lighting, and so on. If you want to use these datasets for non-commercial purposes, please cite the following papers: @article{nowroozi2020survey, title={A survey of machine learning techniques in adversarial image forensics}, author={Nowroozi, Ehsan and Dehghantanha, Ali and Parizi, Reza M and Choo, Kim-Kwang Raymond}, journal={Computers \& Security}, pages={102092}, year={2020}, publisher={Elsevier}}