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In this work, we present a novel framework for camera relocation inautonomous vehicles, leveraging deep neural networks (DNN). While existingliterature offers various DNN-based camera relocation methods, their deploymentis hindered by their high computational demands during inference. In contrast,our approach addresses this challenge through edge cloud collaboration.Specifically, we strategically offload certain modules of the neural network tothe server and evaluate the inference time of data frames under differentnetwork segmentation schemes to guide our offloading decisions. Our findingshighlight the vital role of server-side offloading in DNN-based camerarelocation for autonomous vehicles, and we also discuss the results of datafusion. Finally, we validate the effectiveness of our proposed frameworkthrough experimental evaluation.

Improving Efficiency of DNN-based Relocalization Module for Autonomous Driving with Server-side Computing