# Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis

arXiv: https://arxiv.org/abs/1810.11610 · HTML: https://mlsanity.com/paper/1810.11610/

## Key facts

- Cited by 59 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Oct 2018.

## Built on by (most cited first, 30 of 59)

- [One-Shot High-Fidelity Talking-Head Synthesis with Deformable Neural Radiance Field](https://mlsanity.com/paper/2304.05097/) (2023)
- [PISE: Person Image Synthesis and Editing with Decoupled GAN](https://mlsanity.com/paper/2103.04023/) (2021)
- [StylePeople: A Generative Model of Fullbody Human Avatars](https://mlsanity.com/paper/2104.08363/) (2021)
- [Learning Semantic Person Image Generation by Region-Adaptive Normalization](https://mlsanity.com/paper/2104.06650/) (2021)
- [ZFlow: Gated Appearance Flow-based Virtual Try-on with 3D Priors](https://mlsanity.com/paper/2109.07001/) (2021)
- [Toward Accurate and Realistic Outfits Visualization with Attention to Details](https://mlsanity.com/paper/2106.06593/) (2021)
- [Bidirectionally Deformable Motion Modulation For Video-based Human Pose Transfer](https://mlsanity.com/paper/2307.07754/) (2023)
- [MV-TON: Memory-based Video Virtual Try-on network](https://mlsanity.com/paper/2108.07502/) (2021)
- [GUAVA: Generalizable Upper Body 3D Gaussian Avatar](https://mlsanity.com/paper/2505.03351/) (2025)
- [Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling](https://mlsanity.com/paper/2103.14338/) (2021)
- [Bi-level Feature Alignment for Versatile Image Translation and Manipulation](https://mlsanity.com/paper/2107.03021/) (2021)
- [CT-Net: Complementary Transfering Network for Garment Transfer with Arbitrary Geometric Changes](https://mlsanity.com/paper/2105.05497/) (2021)
- [3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping](https://mlsanity.com/paper/2212.07378/) (2022)
- [Deep Person Generation: A Survey from the Perspective of Face, Pose and Cloth Synthesis](https://mlsanity.com/paper/2109.02081/) (2021)
- [Learning Realistic Human Reposing using Cyclic Self-Supervision with 3D Shape, Pose, and Appearance Consistency](https://mlsanity.com/paper/2110.05458/) (2021)
- [Human MotionFormer: Transferring Human Motions with Vision Transformers](https://mlsanity.com/paper/2302.11306/) (2023)
- [Copy Motion From One to Another: Fake Motion Video Generation](https://mlsanity.com/paper/2205.01373/) (2022)
- [Flow Guided Transformable Bottleneck Networks for Motion Retargeting](https://mlsanity.com/paper/2106.07771/) (2021)
- [SPG-VTON: Semantic Prediction Guidance for Multi-pose Virtual Try-on](https://mlsanity.com/paper/2108.01578/) (2021)
- [Learning Dense Correspondence for NeRF-Based Face Reenactment](https://mlsanity.com/paper/2312.10422/) (2023)
- [HumanDiffusion: a Coarse-to-Fine Alignment Diffusion Framework for Controllable Text-Driven Person Image Generation](https://mlsanity.com/paper/2211.06235/) (2022)
- [Human Image Generation: A Comprehensive Survey](https://mlsanity.com/paper/2212.08896/) (2022)
- [SCAM! Transferring humans between images with Semantic Cross Attention Modulation](https://mlsanity.com/paper/2210.04883/) (2022)
- [Self-supervised Correlation Mining Network for Person Image Generation](https://mlsanity.com/paper/2111.13307/) (2021)
- [Deep Image Synthesis from Intuitive User Input: A Review and Perspectives](https://mlsanity.com/paper/2107.04240/) (2021)
- [VeRi3D: Generative Vertex-based Radiance Fields for 3D Controllable Human Image Synthesis](https://mlsanity.com/paper/2309.04800/) (2023)
- [Do As I Do: Pose Guided Human Motion Copy](https://mlsanity.com/paper/2406.16601/) (2024)
- [Progressive and Aligned Pose Attention Transfer for Person Image Generation](https://mlsanity.com/paper/2103.11622/) (2021)
- [SCULPT: Shape-Conditioned Unpaired Learning of Pose-dependent Clothed and Textured Human Meshes](https://mlsanity.com/paper/2308.10638/) (2023)
- [Generalizable Face Landmarking Guided by Conditional Face Warping](https://mlsanity.com/paper/2404.12322/) (2024)

## Abstract (arXiv)

Despite remarkable advances in image synthesis research, existing works often fail in manipulating images under the context of large geometric transformations. Synthesizing person images conditioned on arbitrary poses is one of the most representative examples where the generation quality largely relies on the capability of identifying and modeling arbitrary transformations on different body parts. Current generative models are often built on local convolutions and overlook the key challenges (e.g. heavy occlusions, different views or dramatic appearance changes) when distinct geometric changes happen for each part, caused by arbitrary pose manipulations. This paper aims to resolve these challenges induced by geometric variability and spatial displacements via a new Soft-Gated Warping Generative Adversarial Network (Warping-GAN), which is composed of two stages: 1) it first synthesizes a target part segmentation map given a target pose, which depicts the region-level spatial layouts for guiding image synthesis with higher-level structure constraints; 2) the Warping-GAN equipped with a soft-gated warping-block learns feature-level mapping to render textures from the original image into the generated segmentation map. Warping-GAN is capable of controlling different transformation degrees given distinct target poses. Moreover, the proposed warping-block is light-weight and flexible enough to be injected into any networks. Human perceptual studies and quantitative evaluations demonstrate the superiority of our Warping-GAN that significantly outperforms all existing methods on two large datasets.