mlsanityData to 14 Oct 2026

MGT: Extending Virtual Try-Off to Multi-Garment Scenarios

arXiv 2504.13078 ↗First posted 17 Apr 2025cs.CV cs.AIcited by 6

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Abstract (arXiv)

Computer vision is transforming fashion industry through Virtual Try-On (VTON) and Virtual Try-Off (VTOFF). VTON generates images of a person in a specified garment using a target photo and a standardized garment image, while a more challenging variant, Person-to-Person Virtual Try-On (p2p-VTON), uses a photo of another person wearing the garment. VTOFF, in contrast, extracts standardized garment images from photos of clothed individuals. We introduce Multi-Garment TryOffDiff (MGT), a diffusion-based VTOFF model capable of handling diverse garment types, including upper-body, lower-body, and dresses. MGT builds on a latent diffusion architecture with SigLIP-based image conditioning to capture garment characteristics such as shape, texture, and pattern. To address garment diversity, MGT incorporates class-specific embeddings, achieving state-of-the-art VTOFF results on VITON-HD and competitive performance on DressCode. When paired with VTON models, it further enhances p2p-VTON by reducing unwanted attribute transfer, such as skin tone, ensuring preservation of person-specific characteristics. Demo, code, and models are available at: https://rizavelioglu.github.io/tryoffdiff/

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 35 of its 48 references that are in the map. First posted on arXiv 17 Apr 2025.

Builds on

35 of 48 references.

References · 35

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
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  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  4. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  5. 2016Layer Normalizationcited by 5,669
  6. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,503
  7. 2024Scaling Rectified Flow Transformers for High-Resolution Image Synthesiscited by 4,181
  8. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,761
  9. 2023Sigmoid Loss for Language Image Pre-Trainingcited by 3,109
  10. 2022Elucidating the Design Space of Diffusion-Based Generative Modelscited by 3,045
  11. 2021Image Super-Resolution via Iterative Refinementcited by 1,511
  12. 2023IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Modelscited by 1,464
23 more
  1. 2023T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Modelscited by 1,351
  2. 2021Palette: Image-to-Image Diffusion Modelscited by 1,300
  3. 2018Demystifying MMD GANscited by 1,293
  4. 2020Image Quality Assessment: Unifying Structure and Texture Similaritycited by 811
  5. 2023Zero-shot Image-to-Image Translationcited by 505
  6. 2021VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalizationcited by 287
  7. 2017VITON: An Image-based Virtual Try-on Networkcited by 286
  8. 2018Toward Characteristic-Preserving Image-based Virtual Try-On Networkcited by 192
  9. 2022Dress Code: High-Resolution Multi-Category Virtual Try-Oncited by 162
  10. 2024OOTDiffusion: Outfitting Fusion based Latent Diffusion for Controllable Virtual Try-oncited by 151
  11. 2021Parser-Free Virtual Try-on via Distilling Appearance Flowscited by 143
  12. 2024CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Modelscited by 102
  13. 2023Multimodal Garment Designer: Human-Centric Latent Diffusion Models for Fashion Image Editingcited by 62
  14. 2023Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Modelscited by 62
  15. 2021Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GANcited by 40
  16. 2017The Conditional Analogy GAN: Swapping Fashion Articles on People Imagescited by 33
  17. 2024TryOffDiff: Virtual-Try-Off via High-Fidelity Garment Reconstruction using Diffusion Modelscited by 19
  18. 2022ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Designcited by 16
  19. 2024TryOffAnyone: Tiled Cloth Generation from a Dressed Personcited by 16
  20. 2023DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignmentcited by 15
  21. 2024GarmentAligner: Text-to-Garment Generation via Retrieval-augmented Multi-level Correctionscited by 10
  22. 2023ViscoNet: Bridging and Harmonizing Visual and Textual Conditioning for ControlNetcited by 7
  23. 2024IGR: Improving Diffusion Model for Garment Restoration from Person Imagecited by 5

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 5.

6 papers.

  1. 2025Inverse Virtual Try-On: Generating Multi-Category Product-Style Images from Clothed Individualscited by 4
  2. 2026Garments2Look: A Multi-Reference Dataset for High-Fidelity Outfit-Level Virtual Try-On with Clothing and Accessoriescited by 4
  3. 2026OmniDiT: Extending Diffusion Transformer to Omni-VTON Frameworkcited by 1
  4. 2026BridgeDiff: Bridging Human Observations and Flat-Garment Synthesis for Virtual Try-Offcited by 0
  5. 2026Dress-ED: Instruction-Guided Editing for Virtual Try-On and Try-Offcited by 0
  6. 2026TrendGen: An Outfit Recommendation and Display Systemcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026What Matters in Virtual Try-Off? Dual-UNet Diffusion Model For Garment Reconstruction
  2. 2024MV-VTON: Multi-View Virtual Try-On with Diffusion Models
  3. 2026GO-MLVTON: Garment Occlusion-Aware Multi-Layer Virtual Try-On with Diffusion Models
  4. 2024M&M VTO: Multi-Garment Virtual Try-On and Editing
  5. 2025MuGa-VTON: Multi-Garment Virtual Try-On via Diffusion Transformers with Prompt Customization
  6. 2024Improving Diffusion Models for Authentic Virtual Try-on in the Wild
  7. 2025MFP-VTON: Enhancing Mask-Free Person-to-Person Virtual Try-On via Diffusion Transformer
  8. 2024PFDM: Parser-Free Virtual Try-on via Diffusion Model