mlsanityData to 14 Oct 2026

Dress&Dance: Dress up and Dance as You Like It - Technical Preview

arXiv 2508.21070 ↗First posted 28 Aug 2025cs.CV cs.LGcited by 2

On the map: Diffusion models → 3D, point cloud and scene generation

Abstract (arXiv)

We present Dress&Dance, a video diffusion framework that generates high quality 5-second-long 24 FPS virtual try-on videos at 1152x720 resolution of a user wearing desired garments while moving in accordance with a given reference video. Our approach requires a single user image and supports a range of tops, bottoms, and one-piece garments, as well as simultaneous tops and bottoms try-on in a single pass. Key to our framework is CondNet, a novel conditioning network that leverages attention to unify multi-modal inputs (text, images, and videos), thereby enhancing garment registration and motion fidelity. CondNet is trained on heterogeneous training data, combining limited video data and a larger, more readily available image dataset, in a multistage progressive manner. Dress&Dance outperforms existing open source and commercial solutions and enables a high quality and flexible try-on experience.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 28 of its 32 references that are in the map. First posted on arXiv 28 Aug 2025.

Builds on

28 of 32 references.

Closest ancestors · 6

Same direction, newest first

  1. 2024Fashion-VDM: Video Diffusion Model for Virtual Try-On31 Oct
  2. 2024WildVidFit: Video Virtual Try-On in the Wild via Image-Based Controlled Diffusion Models15 Jul
  3. 2024Texture-Preserving Diffusion Models for High-Fidelity Virtual Try-On1 Apr
  4. 2024StableGarment: Garment-Centric Generation via Stable Diffusion16 Mar
  5. 2024OOTDiffusion: Outfitting Fusion based Latent Diffusion for Controllable Virtual Try-on4 Mar
  6. 2023StableVITON: Learning Semantic Correspondence with Latent Diffusion Model for Virtual Try-On4 Dec

Other references · 22

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  2. 2023GPT-4 Technical Reportcited by 18,396
  3. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  4. 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,581
  5. 2024CogVideoX: Text-to-Video Diffusion Models with An Expert Transformercited by 2,261
  6. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,937
  7. 2024Evaluating Text-to-Visual Generation with Image-to-Text Generationcited by 474
  8. 2023I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Modelscited by 350
  9. 2021Parser-Free Virtual Try-on via Distilling Appearance Flowscited by 143
  10. 2023TryOnDiffusion: A Tale of Two UNetscited by 141
  11. 2022High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditionscited by 130
  12. 2023GP-VTON: Towards General Purpose Virtual Try-on via Collaborative Local-Flow Global-Parsing Learningcited by 120
10 more
  1. 2023Reuse and Diffuse: Iterative Denoising for Text-to-Video Generationcited by 50
  2. 2024Tunnel Try-on: Excavating Spatial-temporal Tunnels for High-quality Virtual Try-on in Videoscited by 32
  3. 2024M&M VTO: Multi-Garment Virtual Try-On and Editingcited by 29
  4. 2024Videoshop: Localized Semantic Video Editing with Noise-Extrapolated Diffusion Inversioncited by 27
  5. 2022ClothFormer:Taming Video Virtual Try-on in All Modulecited by 26
  6. 2021MV-TON: Memory-based Video Virtual Try-on networkcited by 23
  7. 2023BIVDiff: A Training-Free Framework for General-Purpose Video Synthesis via Bridging Image and Video Diffusion Modelscited by 20
  8. 2020ShineOn: Illuminating Design Choices for Practical Video-based Virtual Clothing Try-oncited by 14
  9. 2024D4-VTON: Dynamic Semantics Disentangling for Differential Diffusion based Virtual Try-Oncited by 14
  10. 2024TryOn-Adapter: Efficient Fine-Grained Clothing Identity Adaptation for High-Fidelity Virtual Try-Oncited by 3

Built on by

Cited by year (2026 to 14 Oct)

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

2 papers.

  1. 2025Virtual Fitting Room: Generating Arbitrarily Long Videos of Virtual Try-On from a Single Image -- Technical Previewcited by 0
  2. 2026TexTailor: Texture-Preserving Video Virtual Try-On via Adaptive Garment Conditioningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024VITON-DiT: Learning In-the-Wild Video Try-On from Human Dance Videos via Diffusion Transformers
  2. 2025MagicTryOn: Harnessing Diffusion Transformer for Garment-Preserving Video Virtual Try-on
  3. 2025Once Is Enough: Lightweight DiT-Based Video Virtual Try-On via One-Time Garment Appearance Injection
  4. 2025The devil is in the details: Enhancing Video Virtual Try-On via Keyframe-Driven Details Injection
  5. 2025Pursuing Temporal-Consistent Video Virtual Try-On via Dynamic Pose Interaction
  6. 2023DreamPose: Fashion Image-to-Video Synthesis via Stable Diffusion
  7. 2026iTryOn: Mastering Interactive Video Virtual Try-On with Spatial-Semantic Guidance
  8. 2024DiffusionTrend: A Minimalist Approach to Virtual Fashion Try-On