# Emotion Transfer Using Vector-Valued Infinite Task Learning

arXiv: https://arxiv.org/abs/2102.05075 · HTML: https://mlsanity.com/paper/2102.05075/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 21 of its 57 references that are in the map.
- First posted on arXiv 9 Feb 2021.

## Builds on (most cited first, 21 of 21)

- [Perceptual Losses for Real-Time Style Transfer and Super-Resolution](https://mlsanity.com/paper/1603.08155/) (2016)
- [ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness](https://mlsanity.com/paper/1811.12231/) (2018)
- [StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation](https://mlsanity.com/paper/1711.09020/) (2017)
- [AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild](https://mlsanity.com/paper/1708.03985/) (2017)
- [Neural Style Transfer: A Review](https://mlsanity.com/paper/1705.04058/) (2017)
- [Texture Networks: Feed-forward Synthesis of Textures and Stylized Images](https://mlsanity.com/paper/1603.03417/) (2016)
- [GANimation: Anatomically-aware Facial Animation from a Single Image](https://mlsanity.com/paper/1807.09251/) (2018)
- [Style Transfer in Text: Exploration and Evaluation](https://mlsanity.com/paper/1711.06861/) (2017)
- [Learning Deep Kernels for Non-Parametric Two-Sample Tests](https://mlsanity.com/paper/2002.09116/) (2020)
- [Kernel methods through the roof: handling billions of points efficiently](https://mlsanity.com/paper/2006.10350/) (2020)
- [FALKON: An Optimal Large Scale Kernel Method](https://mlsanity.com/paper/1705.10958/) (2017)
- [Operator-valued Kernels for Learning from Functional Response Data](https://mlsanity.com/paper/1510.08231/) (2015)
- [ExprGAN: Facial Expression Editing with Controllable Expression Intensity](https://mlsanity.com/paper/1709.03842/) (2017)
- [A Compact Embedding for Facial Expression Similarity](https://mlsanity.com/paper/1811.11283/) (2018)
- [Geometry Guided Adversarial Facial Expression Synthesis](https://mlsanity.com/paper/1712.03474/) (2017)
- [High Resolution Face Age Editing](https://mlsanity.com/paper/2005.04410/) (2020)
- [Geometry-Contrastive GAN for Facial Expression Transfer](https://mlsanity.com/paper/1802.01822/) (2018)
- [Audio style transfer](https://mlsanity.com/paper/1710.11385/) (2017)
- [Unsupervised Learning of Artistic Styles with Archetypal Style Analysis](https://mlsanity.com/paper/1805.11155/) (2018)
- [I Know How You Feel: Emotion Recognition with Facial Landmarks](https://mlsanity.com/paper/1805.00326/) (2018)
- [Infinite-Task Learning with RKHSs](https://mlsanity.com/paper/1805.08809/) (2018)

## Abstract (arXiv)

Style transfer is a significant problem of machine learning with numerous successful applications. In this work, we present a novel style transfer framework building upon infinite task learning and vector-valued reproducing kernel Hilbert spaces. We instantiate the idea in emotion transfer where the goal is to transform facial images to different target emotions. The proposed approach provides a principled way to gain explicit control over the continuous style space. We demonstrate the efficiency of the technique on popular facial emotion benchmarks, achieving low reconstruction cost and high emotion classification accuracy.