# Text Guided Person Image Synthesis

arXiv: https://arxiv.org/abs/1904.05118 · HTML: https://mlsanity.com/paper/1904.05118/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Apr 2019.

## Built on by (most cited first, 22 of 22)

- [Speech2AffectiveGestures: Synthesizing Co-Speech Gestures with Generative Adversarial Affective Expression Learning](https://mlsanity.com/paper/2108.00262/) (2021)
- [Make-An-Animation: Large-Scale Text-conditional 3D Human Motion Generation](https://mlsanity.com/paper/2305.09662/) (2023)
- [DAE-GAN: Dynamic Aspect-aware GAN for Text-to-Image Synthesis](https://mlsanity.com/paper/2108.12141/) (2021)
- [PoseFix: Correcting 3D Human Poses with Natural Language](https://mlsanity.com/paper/2309.08480/) (2023)
- [Text2Human: Text-Driven Controllable Human Image Generation](https://mlsanity.com/paper/2205.15996/) (2022)
- [QuantArt: Quantizing Image Style Transfer Towards High Visual Fidelity](https://mlsanity.com/paper/2212.10431/) (2022)
- [Deep Person Generation: A Survey from the Perspective of Face, Pose and Cloth Synthesis](https://mlsanity.com/paper/2109.02081/) (2021)
- [The Image Local Autoregressive Transformer](https://mlsanity.com/paper/2106.02514/) (2021)
- [BM-NAS: Bilevel Multimodal Neural Architecture Search](https://mlsanity.com/paper/2104.09379/) (2021)
- [AttrLostGAN: Attribute Controlled Image Synthesis from Reconfigurable Layout and Style](https://mlsanity.com/paper/2103.13722/) (2021)
- [TIPS: Text-Induced Pose Synthesis](https://mlsanity.com/paper/2207.11718/) (2022)
- [Human Image Generation: A Comprehensive Survey](https://mlsanity.com/paper/2212.08896/) (2022)
- [Conditional Temporal Variational AutoEncoder for Action Video Prediction](https://mlsanity.com/paper/2108.05658/) (2021)
- [Towards Better Adversarial Synthesis of Human Images from Text](https://mlsanity.com/paper/2107.01869/) (2021)
- [Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry](https://mlsanity.com/paper/2111.00905/) (2021)
- [Explaining Vision and Language through Graphs of Events in Space and Time](https://mlsanity.com/paper/2309.08612/) (2023)
- [Human Silhouette and Skeleton Video Synthesis through Wi-Fi signals](https://mlsanity.com/paper/2203.05864/) (2022)
- [Text-Conditional Contextualized Avatars For Zero-Shot Personalization](https://mlsanity.com/paper/2304.07410/) (2023)
- [fAshIon after fashion: A Report of AI in Fashion](https://mlsanity.com/paper/2105.03050/) (2021)
- [GUNet: A Graph Convolutional Network United Diffusion Model for Stable and Diversity Pose Generation](https://mlsanity.com/paper/2409.11689/) (2024)
- [Semantically Consistent Person Image Generation](https://mlsanity.com/paper/2302.14728/) (2023)
- [GEST: the Graph of Events in Space and Time as a Common Representation between Vision and Language](https://mlsanity.com/paper/2305.12940/) (2023)

## Abstract (arXiv)

This paper presents a novel method to manipulate the visual appearance (pose and attribute) of a person image according to natural language descriptions. Our method can be boiled down to two stages: 1) text guided pose generation and 2) visual appearance transferred image synthesis. In the first stage, our method infers a reasonable target human pose based on the text. In the second stage, our method synthesizes a realistic and appearance transferred person image according to the text in conjunction with the target pose. Our method extracts sufficient information from the text and establishes a mapping between the image space and the language space, making generating and editing images corresponding to the description possible. We conduct extensive experiments to reveal the effectiveness of our method, as well as using the VQA Perceptual Score as a metric for evaluating the method. It shows for the first time that we can automatically edit the person image from the natural language descriptions.