# Real-Time Portrait Stylization on the Edge

arXiv: https://arxiv.org/abs/2206.01244 · HTML: https://mlsanity.com/paper/2206.01244/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 23 of its 27 references that are in the map.
- First posted on arXiv 2 Jun 2022.

## Builds on (most cited first, 23 of 23)

- [Image-to-Image Translation with Conditional Adversarial Networks](https://mlsanity.com/paper/1611.07004/) (2016)
- [Analyzing and Improving the Image Quality of StyleGAN](https://mlsanity.com/paper/1912.04958/) (2019)
- [Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation](https://mlsanity.com/paper/1308.3432/) (2013)
- [Learning both Weights and Connections for Efficient Neural Networks](https://mlsanity.com/paper/1506.02626/) (2015)
- [Neural Architecture Search with Reinforcement Learning](https://mlsanity.com/paper/1611.01578/) (2016)
- [Multimodal Unsupervised Image-to-Image Translation](https://mlsanity.com/paper/1804.04732/) (2018)
- [Channel Pruning for Accelerating Very Deep Neural Networks](https://mlsanity.com/paper/1707.06168/) (2017)
- [Contrastive Learning for Unpaired Image-to-Image Translation](https://mlsanity.com/paper/2007.15651/) (2020)
- [Unsupervised Image-to-Image Translation Networks](https://mlsanity.com/paper/1703.00848/) (2017)
- [DRIT++: Diverse Image-to-Image Translation via Disentangled Representations](https://mlsanity.com/paper/1905.01270/) (2019)
- [Few-Shot Unsupervised Image-to-Image Translation](https://mlsanity.com/paper/1905.01723/) (2019)
- [U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation](https://mlsanity.com/paper/1907.10830/) (2019)
- [Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation](https://mlsanity.com/paper/1904.06807/) (2019)
- [AttentionGAN: Unpaired Image-to-Image Translation using Attention-Guided Generative Adversarial Networks](https://mlsanity.com/paper/1911.11897/) (2019)
- [AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks](https://mlsanity.com/paper/2006.08198/) (2020)
- [GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework](https://mlsanity.com/paper/2008.11062/) (2020)
- [Teachers Do More Than Teach: Compressing Image-to-Image Models](https://mlsanity.com/paper/2103.03467/) (2021)
- [GANs Can Play Lottery Tickets Too](https://mlsanity.com/paper/2106.00134/) (2021)
- [Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework](https://mlsanity.com/paper/2012.04240/) (2020)
- [AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation](https://mlsanity.com/paper/2102.12593/) (2021)
- [DAIS: Automatic Channel Pruning via Differentiable Annealing Indicator Search](https://mlsanity.com/paper/2011.02166/) (2020)
- [GANs N' Roses: Stable, Controllable, Diverse Image to Image Translation (works for videos too!)](https://mlsanity.com/paper/2106.06561/) (2021)
- [Generative Adversarial Networks for photo to Hayao Miyazaki style cartoons](https://mlsanity.com/paper/2005.07702/) (2020)

## Abstract (arXiv)

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 10× computation reduction on the generative model and achieve real-time video stylization on off-the-shelf smartphone using mobile GPUs.