[ACM MM 2023] - LaDI-VTON: Latent Diffusion Textual-Inversion Enhanced Virtual Try-On
fashionai 开源项目推荐(40 个)
fashionai 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 40 个仓库[ICCV 2023] This is the official repository for the paper "Multimodal Garment Designer: Human-Centric Latent Diffusion Models for Fashion Image Editing"
Full pipeline for TianChi FashionAI clothes keypoints detection compitetion in TensorFlow
[ACM TIST 2025]GenAI in Fashion:概述,还包括🔥最新论文、⚙️指标、👀研讨会、🚀公司与产品等)
Context-Aware Visual Compatibility Prediction (https://arxiv.org/abs/1902.03646)
FashionAI Clothes Attribute Recognition
FashionAI Global Challenge—Attributes Recognition of Apparel based on PyTorch
This is the official repository for the paper "OpenFashionCLIP: Vision-and-Language Contrastive Learning with Open-Source Fashion Data". ICIAP 2023
A tensorflow model for segmentation of fashion items out of multiple product images
pytorch implementation of the deepfashion architecture (https://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Liu_DeepFashion_Powering_Robust_CVPR_2016_paper.pdf)
MAD: Makeup All-in-One with Cross-Domain Diffusion Model
👕👖🥻Implementations of AI for my UG Project-"Generative Models and Recommender Systems for AI-driven Fashion"
Fashion Item segmentation with Mask_RCNN
FashionAI全球挑战赛——服饰关键点定位
Dress styles generation using GANs using TensorFlow
AI technology to make Lego characters by analyzing the clothes and physical gender you are wearing.
Code for FashionAI KeyPoint Detection Challenge
Attributes Recognition of Apparel
Fashion trend prediction as part of team Maverick for club DSC at UTD.
Fashion-AI is a PyTorch code base that implements various sate-of-the-art algorithms related to fashion AI, e.g., compatibility prediction, outfit recommendation, etc.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/fashionai。
- 该话题在 GitHub 上共有 40 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 2203 Star,覆盖 4 种主要语言,数据更新于 2026-11-08。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。