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Significance of Anatomical Constraints in Virtual Try-On

arXiv 2401.02110 ↗First posted 4 Jan 2024cs.CVcited by 0

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Abstract (arXiv)

The system of Virtual Try-ON (VTON) allows a user to try a product virtually. In general, a VTON system takes a clothing source and a person's image to predict the try-on output of the person in the given clothing. Although existing methods perform well for simple poses, in case of bent or crossed arms posture or when there is a significant difference between the alignment of the source clothing and the pose of the target person, these methods fail by generating inaccurate clothing deformations. In the VTON methods that employ Thin Plate Spline (TPS) based clothing transformations, this mainly occurs for two reasons - (1)~the second-order smoothness constraint of TPS that restricts the bending of the object plane. (2)~Overlaps among different clothing parts (e.g., sleeves and torso) can not be modeled by a single TPS transformation, as it assumes the clothing as a single planar object; therefore, disregards the independence of movement of different clothing parts. To this end, we make two major contributions. Concerning the bending limitations of TPS, we propose a human AnaTomy-Aware Geometric (ATAG) transformation. Regarding the overlap issue, we propose a part-based warping approach that divides the clothing into independently warpable parts to warp them separately and later combine them. Extensive analysis shows the efficacy of this approach.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 27 of its 49 references that are in the map. First posted on arXiv 4 Jan 2024.

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27 of 49 references.

References · 27

  1. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  2. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,451
  3. 2017Non-local Neural Networkscited by 2,290
  4. 2016Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,061
  5. 2018DensePose: Dense Human Pose Estimation In The Wildcited by 573
  6. 2018Image Inpainting for Irregular Holes Using Partial Convolutionscited by 505
  7. 2021VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalizationcited by 287
  8. 2017VITON: An Image-based Virtual Try-on Networkcited by 285
  9. 2018Toward Characteristic-Preserving Image-based Virtual Try-On Networkcited by 192
  10. 2016View Synthesis by Appearance Flowcited by 172
  11. 2019Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesiscited by 161
  12. 2020Controllable Person Image Synthesis with Attribute-Decomposed GANcited by 150
15 more
  1. 2020Towards Photo-Realistic Virtual Try-On by Adaptively GeneratingleftrightarrowPreserving Image Contentcited by 148
  2. 2021Parser-Free Virtual Try-on via Distilling Appearance Flowscited by 142
  3. 2023GP-VTON: Towards General Purpose Virtual Try-on via Collaborative Local-Flow Global-Parsing Learningcited by 120
  4. 2017Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsingcited by 109
  5. 2019Towards Multi-pose Guided Virtual Try-on Networkcited by 95
  6. 2022Style-Based Global Appearance Flow for Virtual Try-Oncited by 88
  7. 2022Single Stage Virtual Try-on via Deformable Attention Flowscited by 64
  8. 2021Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GANcited by 40
  9. 2021ZFlow: Gated Appearance Flow-based Virtual Try-on with 3D Priorscited by 34
  10. 2022C-VTON: Context-Driven Image-Based Virtual Try-On Networkcited by 29
  11. 2018M2E-Try On Net: Fashion from Model to Everyonecited by 27
  12. 2020SieveNet: A Unified Framework for Robust Image-Based Virtual Try-Oncited by 23
  13. 2020GarmentGAN: Photo-realistic Adversarial Fashion Transfercited by 16
  14. 2019Generating High-Resolution Fashion Model Images Wearing Custom Outfitscited by 15
  15. 2020LGVTON: A Landmark Guided Approach to Virtual Try-Oncited by 6

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