Inverse Garment and Pattern Modeling with a Differentiable Simulator: Enhancing Virtual Try-On and Fabrication

Kernekoncepter

The author's main thesis is to develop a method using a differentiable simulator to recover 2D sewing patterns from 3D garment geometries, enabling faithful replication of garment shapes for virtual try-on and fabrication.

Resumé

The content discusses a novel approach to inverse garment design, focusing on recovering 2D sewing patterns from 3D garment geometries using a differentiable simulator. The method aims to enhance virtual try-on experiences and facilitate fabrications by faithfully replicating intricate garment shapes. By optimizing pattern alterations through simulation-driven processes, the system demonstrates promising results across various garment types.
Key points include:

• Introduction of an innovative method for inverse garment design focusing on recovering 2D sewing patterns from 3D geometries.
• Utilization of a differentiable cloth simulator for accurate pattern estimation and faithful replication of draped garments.
• Validation of the approach on different garment types showcasing improved pattern estimations compared to state-of-the-art methods.
• Detailed explanation of the optimization process for pattern alteration based on simulation results.
• Evaluation metrics used to compare the performance of the proposed method with existing approaches in terms of accuracy and efficiency.
• Discussion on the impact of the developed system on fields like virtual try-on experiences and fabrications in the fashion industry.

The content provides insights into cutting-edge technology that can revolutionize how garments are designed, simulated, and produced in virtual environments.

Statistik

"Our generated data and code will be made available for research purposes at https://anonymous.project.website."
"We set one time step ∆t to 0.05s."
"The number of time steps for one forward simulation between 10 and 20."
"By vectorizing as much as possible the force and jacobian computation, our extension to ARCSim differentiable cloth simulator allows to run all its computations on a GPU."

Citater

"We validate our approach on examples of different garment types, showing that our method faithfully reproduces both draped garment shape and sewing pattern."
"Our approach does not require a lot of data but is capable of faithfully replicating intricate garment shape due to its understanding of physics."
"Our method improves speed efficiency compared to baseline models, especially during reverse processes."
"Our work is similar in spirit to that of Yang et al., who use search-based optimization to recover both 2D sewing patterns and the 3D garment."
"Our system operates based on user-selected base pattern mesh and its corresponding sewn 3D garment, effectively disentangling shape deformations during simulation."

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Inverse Garment and Pattern Modeling with a Differentiable Simulator

by Boyang Yu,Fr... kl. arxiv.org 03-12-2024

https://arxiv.org/pdf/2403.06841.pdf

Dybere Forespørgsler

How might this innovative technology impact traditional fashion design processes beyond virtual applications

This innovative technology could revolutionize traditional fashion design processes beyond virtual applications by streamlining the garment production workflow. By automating the process of generating simulation-ready garment models from 3D shapes, designers can save time and resources typically spent on manual pattern-making and prototyping. This efficiency can lead to faster product development cycles, allowing for more frequent releases and a quicker response to market trends. Additionally, the ability to accurately replicate intricate garment shapes and sewing patterns through inverse simulation opens up new possibilities for customization and personalization in fashion design. Designers can experiment with complex designs without the constraints of traditional pattern-making techniques, leading to more creative and unique garments.

What potential challenges or limitations could arise when implementing this method in real-world fabrications

Implementing this method in real-world fabrications may present challenges related to material properties, manufacturing processes, and scalability. One potential limitation is the accuracy of physical parameter recovery during simulation-based pattern alteration. Variations in fabric elasticity, thickness, or drape behavior may not always be accurately captured by the model, leading to discrepancies between simulated results and actual fabric behavior. Another challenge could arise from translating virtual patterns into physical garments efficiently. Ensuring that the generated patterns are compatible with standard manufacturing techniques while maintaining their fidelity to the original design poses a significant hurdle. Moreover, scaling up this technology for mass production would require robust optimization algorithms capable of handling large datasets efficiently.

How could advancements in virtual modeling like this lead to new opportunities or disruptions in other industries outside fashion

Advancements in virtual modeling like this have the potential to disrupt various industries beyond fashion by enabling realistic simulations for diverse applications such as medical training simulations (e.g., surgical draping), architectural visualization (e.g., simulating fabric structures in interior design), automotive engineering (e.g., testing vehicle upholstery designs), and even entertainment (e.g., creating lifelike digital characters with dynamic clothing). The ability to simulate cloth behavior realistically opens up new opportunities for interactive experiences in gaming or virtual reality environments where clothing plays a crucial role in character representation. Furthermore, these advancements could find applications in fields like sports equipment design (e.g., optimizing performance apparel) or furniture design (e.g., simulating upholstery materials) where understanding fabric interactions is essential for product development.