mlsanityData to 14 Oct 2026

Textile IR: A Bidirectional Intermediate Representation for Physics-Aware Fashion CAD

arXiv 2601.02792 ↗First posted 6 Jan 2026cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

We introduce Textile IR, a bidirectional intermediate representation that connects manufacturing-valid CAD, physics-based simulation, and lifecycle assessment for fashion design. Unlike existing siloed tools where pattern software guarantees sewable outputs but understands nothing about drape, and physics simulation predicts behaviour but cannot automatically fix patterns, Textile IR provides the semantic glue for integration through a seven-layer Verification Ladder -- from cheap syntactic checks (pattern closure, seam compatibility) to expensive physics validation (drape simulation, stress analysis). The architecture enables bidirectional feedback: simulation failures suggest pattern modifications; material substitutions update sustainability estimates in real time; uncertainty propagates across the pipeline with explicit confidence bounds. We formalise fashion engineering as constraint satisfaction over three domains and demonstrate how Textile IR's scene-graph representation enables AI systems to manipulate garments as structured programs rather than pixel arrays. The framework addresses the compound uncertainty problem: when measurement errors in material testing, simulation approximations, and LCA database gaps combine, sustainability claims become unreliable without explicit uncertainty tracking. We propose six research priorities and discuss deployment considerations for fashion SMEs where integrated workflows reduce specialised engineering requirements. Key contribution: a formal representation that makes engineering constraints perceptible, manipulable, and immediately consequential -- enabling designers to navigate sustainability, manufacturability, and aesthetic tradeoffs simultaneously rather than discovering conflicts after costly physical prototyping.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 18 of its 97 references that are in the map. First posted on arXiv 6 Jan 2026.

Builds on

18 of 97 references.

References · 18

  1. 2020Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertaintycited by 129
  2. 2021gradSim: Differentiable simulation for system identification and visuomotor controlcited by 100
  3. 2024DressCode: Autoregressively Sewing and Generating Garments from Text Guidancecited by 44
  4. 2025UXAgent: An LLM Agent-Based Usability Testing Framework for Web Designcited by 40
  5. 2024GarmentCodeData: A Dataset of 3D Made-to-Measure Garments With Sewing Patternscited by 28
  6. 2025Generative and Malleable User Interfaces with Generative and Evolving Task-Driven Data Modelcited by 26
  7. 2025Dress-1-to-3: Single Image to Simulation-Ready 3D Outfit with Diffusion Prior and Differentiable Physicscited by 20
  8. 2023Image-Based Virtual Try-On: A Surveycited by 19
  9. 2022Structure-Preserving 3D Garment Modeling with Neural Sewing Machinescited by 18
  10. 2024Design2GarmentCode: Turning Design Concepts to Tangible Garments Through Program Synthesiscited by 18
  11. 2024RAGDiffusion: Faithful Cloth Generation via External Knowledge Assimilationcited by 9
  12. 2025MPMAvatar: Learning 3D Gaussian Avatars with Accurate and Robust Physics-Based Dynamicscited by 8
6 more
  1. 2024Shaping Realities: Enhancing 3D Generative AI with Fabrication Constraintscited by 6
  2. 2024Estimating Cloth Elasticity Parameters From Homogenized Yarn-Level Modelscited by 3
  3. 2025A Text-to-3D Framework for Joint Generation of CG-Ready Humans and Compatible Garmentscited by 2
  4. 2025D-Garment: Physically Grounded Latent Diffusion for Dynamic Garment Deformationscited by 2
  5. 2025SpringTime: Learning Simulatable Models of Cloth with Spatially-varying Constitutive Propertiescited by 2
  6. 2025AvatarVTON: 4D Virtual Try-On for Animatable Avatarscited by 1

Built on by

Not cited yet.