The Computer Vision for Embedded Systems (CVES) team will investigate methods to improve efficiency (inference time, training time, storage space, energy consumption) of computer vision (both image and multimedia) so that computer vision can run on embedded systems. The team will evaluate how existing methods (such as quantization and pruning) can be applied to new neural architectures (such as transformers). The team will also investigate new architectures of neural networks and compare their efficiency with different levels of accuracy.