Deep Learning Empowers Accurate Body Shape Classification for Personalized Fashion Recommendations
This paper proposes a robust deep learning-based model for accurately classifying human body shapes into five categories - Rectangle, Triangle, Inverted Triangle, Hourglass, and Apple. The model utilizes a segmentation network to extract the person's body from the image, and then employs various pre-trained convolutional neural network architectures to classify the body shape.
Inverse Garment and Pattern Modeling with a Differentiable Simulator: A Detailed Analysis
Die Arbeit konzentriert sich auf die inverse Modellierung von Kleidungsstücken mit einem differenzierbaren Simulator.
DiFashion: Personalized Outfit Generation and Recommendation
Personalized outfit generation through DiFashion enhances fashion recommendation with high fidelity and compatibility.
HAIFIT: Human-Centered AI for Fashion Image Translation
HAIFIT introduces a novel approach to transform sketches into high-fidelity clothing images, excelling in preserving intricate details essential for fashion design applications.
Unveiling a Million High-Quality Fashion Images for Text-to-Image Synthesis in Fashion Design
AI and fashion design merge with the Fashion-Diffusion dataset, offering over a million high-quality images for Text-to-Image synthesis in fashion design.
DiFashion: Personalized Outfit Generation and Recommendation
AI-driven DiFashion enhances personalized outfit generation and recommendation through innovative generative models.
HAIFIT: Human-Centered AI for Fashion Image Translation
Introducing HAIFIT, a novel approach transforming sketches into high-fidelity clothing images, excelling in preserving intricate details essential for fashion design applications.
Inverse Garment and Pattern Modeling with a Differentiable Simulator: Enhancing Virtual Try-On and Fabrication
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.
FashionReGen: LLM-Empowered Fashion Report Generation Study
The author proposes an intelligent Fashion Analyzing and Reporting system, GPT-FAR, to automate the Fashion Report Generation task using Large Language Models (LLMs) in the fashion domain.
DiFashion: Personalized Outfit Generation and Recommendation
DiFashion introduces a novel task, Generative Outfit Recommendation (GOR), to synthesize personalized outfits using AI-generated content. The model aims to achieve high fidelity, compatibility, and personalization in outfit generation.
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