# Detailed Garment Recovery from a Single-View Image

arXiv: https://arxiv.org/abs/1608.01250 · HTML: https://mlsanity.com/paper/1608.01250/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Aug 2016.

## Built on by (most cited first, 16 of 16)

- [SCALE: Modeling Clothed Humans with a Surface Codec of Articulated Local Elements](https://mlsanity.com/paper/2104.07660/) (2021)
- [Disentangled Cycle Consistency for Highly-realistic Virtual Try-On](https://mlsanity.com/paper/2103.09479/) (2021)
- [Structure-Preserving 3D Garment Modeling with Neural Sewing Machines](https://mlsanity.com/paper/2211.06701/) (2022)
- [Human Image Generation: A Comprehensive Survey](https://mlsanity.com/paper/2212.08896/) (2022)
- [Neural Garment Dynamics via Manifold-Aware Transformers](https://mlsanity.com/paper/2407.06101/) (2024)
- [GarmentCrafter: Progressive Novel View Synthesis for Single-View 3D Garment Reconstruction and Editing](https://mlsanity.com/paper/2503.08678/) (2025)
- [Neural 3D Clothes Retargeting from a Single Image](https://mlsanity.com/paper/2102.00062/) (2021)
- [SPnet: Estimating Garment Sewing Patterns from a Single Image](https://mlsanity.com/paper/2312.16264/) (2023)
- [Smart Fashion: A Review of AI Applications in the Fashion & Apparel Industry](https://mlsanity.com/paper/2111.00905/) (2021)
- [Cloth2Body: Generating 3D Human Body Mesh from 2D Clothing](https://mlsanity.com/paper/2309.16189/) (2023)
- [Progressive Limb-Aware Virtual Try-On](https://mlsanity.com/paper/2503.12588/) (2025)
- [PT-VTON: an Image-Based Virtual Try-On Network with Progressive Pose Attention Transfer](https://mlsanity.com/paper/2111.12167/) (2021)
- [NGL: Natural Garment Language for Training-Free Sewing Pattern Estimation](https://mlsanity.com/paper/2602.20700/) (2026)
- [Towards Using Clothes Style Transfer for Scenario-aware Person Video Generation](https://mlsanity.com/paper/2110.11894/) (2021)
- [AIpparel: A Multimodal Foundation Model for Digital Garments](https://mlsanity.com/paper/2412.03937/) (2024)
- [Stitched Embeddings: A Unified Latent Space for 3D Garments and 2D Patterns](https://mlsanity.com/paper/2607.00829/) (2026)

## Abstract (arXiv)

Most recent garment capturing techniques rely on acquiring multiple views of clothing, which may not always be readily available, especially in the case of pre-existing photographs from the web. As an alternative, we pro- pose a method that is able to compute a rich and realistic 3D model of a human body and its outfits from a single photograph with little human in- teraction. Our algorithm is not only able to capture the global shape and geometry of the clothing, it can also extract small but important details of cloth, such as occluded wrinkles and folds. Unlike previous methods using full 3D information (i.e. depth, multi-view images, or sampled 3D geom- etry), our approach achieves detailed garment recovery from a single-view image by using statistical, geometric, and physical priors and a combina- tion of parameter estimation, semantic parsing, shape recovery, and physics- based cloth simulation. We demonstrate the effectiveness of our algorithm by re-purposing the reconstructed garments for virtual try-on and garment transfer applications, as well as cloth animation for digital characters.