# Pixel-Level Domain Transfer

arXiv: https://arxiv.org/abs/1603.07442 · HTML: https://mlsanity.com/paper/1603.07442/

## Key facts

- Cited by 25 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Mar 2016.

## Built on by (most cited first, 25 of 25)

- [Dress Code: High-Resolution Multi-Category Virtual Try-On](https://mlsanity.com/paper/2204.08532/) (2022)
- [Semi-Supervised and Unsupervised Deep Visual Learning: A Survey](https://mlsanity.com/paper/2208.11296/) (2022)
- [Deep Learning-Enabled Semantic Communication Systems with Task-Unaware Transmitter and Dynamic Data](https://mlsanity.com/paper/2205.00271/) (2022)
- [Deep Person Generation: A Survey from the Perspective of Face, Pose and Cloth Synthesis](https://mlsanity.com/paper/2109.02081/) (2021)
- [Pose-driven Attention-guided Image Generation for Person Re-Identification](https://mlsanity.com/paper/2104.13773/) (2021)
- [Continuous Human Action Recognition for Human-Machine Interaction: A Review](https://mlsanity.com/paper/2202.13096/) (2022)
- [StyleTailor: Towards Personalized Fashion Styling via Hierarchical Negative Feedback](https://mlsanity.com/paper/2508.06555/) (2025)
- [Exploring AI in Fashion: A Review of Aesthetics, Personalization, Virtual Try-On, and Forecasting](https://mlsanity.com/paper/2101.08301/) (2021)
- [Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry](https://mlsanity.com/paper/2111.00905/) (2021)
- [CHIMLE: Conditional Hierarchical IMLE for Multimodal Conditional Image Synthesis](https://mlsanity.com/paper/2211.14286/) (2022)
- [A Novel Application of Image-to-Image Translation: Chromosome Straightening Framework by Learning from a Single Image](https://mlsanity.com/paper/2103.02835/) (2021)
- [MEnsA: Mix-up Ensemble Average for Unsupervised Multi Target Domain Adaptation on 3D Point Clouds](https://mlsanity.com/paper/2304.01554/) (2023)
- [BioGAN: An unpaired GAN-based image to image translation model for microbiological images](https://mlsanity.com/paper/2306.06217/) (2023)
- [BrainVoxGen: Deep learning framework for synthesis of Ultrasound to MRI](https://mlsanity.com/paper/2310.08608/) (2023)
- [Semantic Consistency and Identity Mapping Multi-Component Generative Adversarial Network for Person Re-Identification](https://mlsanity.com/paper/2104.13780/) (2021)
- [Deep Learning Techniques for Visual Counting](https://mlsanity.com/paper/2206.03033/) (2022)
- [On Domain-Specific Pre-Training for Effective Semantic Perception in Agricultural Robotics](https://mlsanity.com/paper/2303.12499/) (2023)
- [Theoretical Insights into CycleGAN: Analyzing Approximation and Estimation Errors in Unpaired Data Generation](https://mlsanity.com/paper/2407.11678/) (2024)
- [Multi-View Image-to-Image Translation Supervised by 3D Pose](https://mlsanity.com/paper/2104.05779/) (2021)
- [Cascading Modular Network (CAM-Net) for Multimodal Image Synthesis](https://mlsanity.com/paper/2106.09015/) (2021)
- [Domain Adaptation and Active Learning for Fine-Grained Recognition in the Field of Biodiversity](https://mlsanity.com/paper/2110.11778/) (2021)
- [OmiTrans: generative adversarial networks based omics-to-omics translation framework](https://mlsanity.com/paper/2111.13785/) (2021)
- [Jamdani Motif Generation using Conditional GAN](https://mlsanity.com/paper/2212.11824/) (2022)
- [MV-Fashion: Towards Enabling Virtual Try-On and Size Estimation with Multi-View Paired Data](https://mlsanity.com/paper/2603.08147/) (2026)
- [Fashion130K: An E-commerce Fashion Dataset for Outfit Generation with Unified Multi-modal Condition](https://mlsanity.com/paper/2605.10127/) (2026)

## Abstract (arXiv)

We present an image-conditional image generation model. The model transfers an input domain to a target domain in semantic level, and generates the target image in pixel level. To generate realistic target images, we employ the real/fake-discriminator as in Generative Adversarial Nets, but also introduce a novel domain-discriminator to make the generated image relevant to the input image. We verify our model through a challenging task of generating a piece of clothing from an input image of a dressed person. We present a high quality clothing dataset containing the two domains, and succeed in demonstrating decent results.