DressCode: ShanghaiTech University Unveils 3D Clothing Generation Framework
Shanghai, China – ShanghaiTech University, in collaboration with the University of Pennsylvaniaand Deemos Technology, has launched DressCode, a groundbreaking 3D clothing generation framework. This innovative platform empowers users to automatically generate 3D clothing modelsin various styles and materials using simple text descriptions.
At the heart of DressCode lies SewingGPT, a core module that enables the framework to understand textprompts and translate them into intricate cutting patterns. These patterns are then combined with physically-based rendering techniques to create lifelike clothing models.
Key Features of DressCode:
- Text-Driven Clothing Generation: Users can input textdescriptions, such as a flowing silk dress with a floral pattern or a tailored leather jacket with a zipper, and DressCode will automatically generate the corresponding 3D clothing model.
- Material and Texture Simulation: DressCodegoes beyond basic shapes and textures. It can generate different materials, like silk, lace, and denim, based on text prompts, and simulate realistic lighting effects to enhance visual realism.
- Semantic Understanding and Pattern Generation: The SewingGPT module analyzes the text input, extracting key features and style requirements. It then translatesthis information into a sequence of cutting pattern tokens, representing the precise design of the garment.
- Physically-Based Rendering: Advanced fabric dynamics algorithms are employed to simulate the natural drape and movement of real-world clothing, ensuring that the generated models appear realistic and dynamic.
Technical Principles Behind DressCode:
- Natural Language Processing (NLP): DressCode utilizes advanced NLP techniques to analyze and understand user text input, capturing crucial features and style preferences.
- Sequence Generation Model: SewingGPT, the core component, employs a Transformer-based decoder architecture to convert text descriptions into a serialized representation (tokens sequence)of the clothing cutting pattern.
- Quantization and Dequantization: The parameters of the clothing pattern are converted into tokens through a quantization process. During the generation process, dequantization is performed to reconstruct the pattern in 3D space.
- Conditional Generation: Leveraging text conditional embedding and cross-attention mechanisms, SewingGPT can generate clothing patterns that align with the provided text prompts.
- Physically-Based Rendering (PBR): DressCode employs PBR technology to generate realistic textures and material effects for the clothing, simulating the reflection and refraction properties of different fabrics under various lighting conditions.
*Fabric Dynamics Simulation: Advanced fabric simulation algorithms are integrated to ensure that the clothing exhibits realistic physical behavior in the virtual environment, such as wrinkles, swaying, and draping.
Applications of DressCode:
- Fashion Design: Designers can leverage DressCode to rapidly generate clothing prototypes based on text descriptions, acceleratingthe design process and enabling rapid iteration.
- Virtual Try-On: E-commerce platforms and fashion brands can utilize DressCode to provide virtual try-on services, allowing customers to experience the fit and appearance of clothing online.
- Game Development: Game designers can use DressCode to quickly generate clothing forgame characters, enriching the visual options within the game.
- Film and Television Production: During the costume preparation phase of film and television productions, DressCode can assist designers in generating clothing concept sketches based on script descriptions.
Availability and Resources:
- Project Website: https://ailb-web.ing.unimore.it/dress-code/dataset
- GitHub Repository: https://github.com/aimagelab/dress-code
- arXiv Technical Paper: https://arxiv.org/abs/2204.08532
DressCode represents a significant advancementin the field of 3D clothing generation, offering a powerful tool for designers, developers, and businesses seeking to revolutionize the way clothing is created and experienced. Its ability to generate realistic and customizable clothing models based on simple text descriptions opens up a world of possibilities for innovation in fashion, entertainment, and beyond.
【source】https://ai-bot.cn/dresscode/
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