mlsanityData to 7 Oct 2026

Wearing the Same Outfit in Different Ways -- A Controllable Virtual Try-on Method

arXiv 2211.16989 ↗First posted 29 Nov 2022cs.GR cs.CVcited by 0

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Abstract (arXiv)

An outfit visualization method generates an image of a person wearing real garments from images of those garments. Current methods can produce images that look realistic and preserve garment identity, captured in details such as collar, cuffs, texture, hem, and sleeve length. However, no current method can both control how the garment is worn -- including tuck or untuck, opened or closed, high or low on the waist, etc.. -- and generate realistic images that accurately preserve the properties of the original garment. We describe an outfit visualization method that controls drape while preserving garment identity. Our system allows instance independent editing of garment drape, which means a user can construct an edit (e.g. tucking a shirt in a specific way) that can be applied to all shirts in a garment collection. Garment detail is preserved by relying on a warping procedure to place the garment on the body and a generator then supplies fine shading detail. To achieve instance independent control, we use control points with garment category-level semantics to guide the warp. The method produces state-of-the-art quality images, while allowing creative ways to style garments, including allowing tops to be tucked or untucked; jackets to be worn open or closed; skirts to be worn higher or lower on the waist; and so on. The method allows interactive control to correct errors in individual renderings too. Because the edits are instance independent, they can be applied to large pools of garments automatically and can be conditioned on garment metadata (e.g. all cropped jackets are worn closed or all bomber jackets are worn closed).

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 27 of its 38 references that are in the map. First posted on arXiv 29 Nov 2022.

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27 of 38 references.

References · 27

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,678
  3. 2015Spatial Transformer Networkscited by 1,423
  4. 2018OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,161
  5. 2018DensePose: Dense Human Pose Estimation In The Wildcited by 573
  6. 2021VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalizationcited by 287
  7. 2018Toward Characteristic-Preserving Image-based Virtual Try-On Networkcited by 192
  8. 2022Dress Code: High-Resolution Multi-Category Virtual Try-Oncited by 161
  9. 2020Controllable Person Image Synthesis with Attribute-Decomposed GANcited by 150
  10. 2020Towards Photo-Realistic Virtual Try-On by Adaptively GeneratingleftrightarrowPreserving Image Contentcited by 148
  11. 2021Parser-Free Virtual Try-on via Distilling Appearance Flowscited by 142
  12. 2017Convolutional neural network architecture for geometric matchingcited by 138
15 more
  1. 2019DeepFashion2: A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Imagescited by 132
  2. 2022High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditionscited by 129
  3. 2018ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositingcited by 90
  4. 2022Style-Based Global Appearance Flow for Virtual Try-Oncited by 88
  5. 2020Do Not Mask What You Do Not Need to Mask: a Parser-Free Virtual Try-Oncited by 77
  6. 2022Single Stage Virtual Try-on via Deformable Attention Flowscited by 64
  7. 2021Disentangled Cycle Consistency for Highly-realistic Virtual Try-Oncited by 62
  8. 2018Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesiscited by 59
  9. 2021Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editingcited by 54
  10. 2017Be Your Own Prada: Fashion Synthesis with Structural Coherencecited by 49
  11. 2017A Generative Model of People in Clothingcited by 37
  12. 2021ZFlow: Gated Appearance Flow-based Virtual Try-on with 3D Priorscited by 34
  13. 2021Toward Accurate and Realistic Outfits Visualization with Attention to Detailscited by 33
  14. 2019Compatible and Diverse Fashion Image Inpaintingcited by 26
  15. 2019Fashion++: Minimal Edits for Outfit Improvementcited by 20

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