no code implementations • 13 Feb 2024 • M. Akin Yilmaz, O. Ugur Ulas, Ahmet Bilican, A. Murat Tekalp
As a remedy, we propose controlling the motion range for flow prediction during inference (to approximately match the range of motions in the training data) by downsampling video frames adaptively according to amount of motion and level of hierarchy in order to compress all B-frames using a single flexible-rate model.
1 code implementation • 28 Jun 2023 • M. Akin Yilmaz, O. Ugur Ulas, A. Murat Tekalp
The lack of ability to adapt the motion compensation model to video content is an important limitation of current end-to-end learned video compression models.