Over the past years, mobile AI-based applications are becoming more and more ubiquitous. Various deep learning models can now be found on any mobile device, starting from smartphones running portrait segmentation, image enhancement, face recognition and natural language processing models, to smart-TV boards coming with sophisticated image super-resolution algorithms. The performance of mobile NPUs and DSPs is also increasing dramatically, making it possible to run complex deep learning models and to achieve fast runtime in the majority of tasks.
While many research works targeted at efficient deep learning models have been proposed recently, the evaluation of the obtained solutions is usually happening on desktop CPUs and GPUs, making it nearly impossible to estimate the actual inference time and memory consumption on real mobile hardware. To address this problem, we introduce the first Mobile AI Workshop, where all deep learning solutions are developed for and evaluated on mobile devices.
Due to the performance of the last-generation mobile AI hardware, the topics considered in this workshop will go beyond the simple classification tasks, and will include such challenging problems as image denoising, HDR photography, accurate depth estimation, learned image ISP pipeline, real-time image and video super-resolution. All information about the challenges, papers, invited talks and workshop industry partners is provided at: https://ai-benchmark.com/workshops/mai/2023/