Arena: A Patch-of-Interest ViT Inference Acceleration System for Edge-Assisted Video Analytics

arXiv:2404.09245v1 Announce Type: cross
Abstract: The advent of edge computing has made real-time intelligent video analytics feasible. Previous works, based on traditional model architecture (e.g., CNN, RNN, etc.), employ various strategies to filter out non-region-of-interest content to minimize bandwidth and computation consumption but show inferior performance in adverse environments. Recently, visual foundation models based on transformers have shown great performance in adverse environments due to their amazing generalization capability. However, they require a large amount of computation power, which limits …

abstract analytics architecture arena arxiv bandwidth cnn computation computing consumption cs.cv cs.mm edge edge computing environments etc filter inference intelligent performance real-time rnn show strategies type video video analytics vit