Real-Time Portrait Stylization on the Edge
Yanyu Li, Xuan Shen, Geng Yuan, Jiexiong Guan, Wei Niu, Hao Tang, Bin, Ren, Yanzhi Wang

TL;DR
This paper presents a real-time portrait stylization method optimized for mobile devices, achieving high-quality cartoon and anime effects with significantly reduced computation.
Contribution
It introduces a latency-driven differentiable architecture search that reduces model complexity and enables real-time stylization on smartphones.
Findings
10x reduction in computation compared to baseline models
Real-time stylization achieved on off-the-shelf smartphones
Maintains high-quality, realistic stylized portraits
Abstract
In this work we demonstrate real-time portrait stylization, specifically, translating self-portrait into cartoon or anime style on mobile devices. We propose a latency-driven differentiable architecture search method, maintaining realistic generative quality. With our framework, we obtain computation reduction on the generative model and achieve real-time video stylization on off-the-shelf smartphone using mobile GPUs.
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Taxonomy
TopicsHuman Motion and Animation · Video Analysis and Summarization · Generative Adversarial Networks and Image Synthesis
