The proposed method is trained and validated using benchmark datasets such as Fashion product images dataset and Shoe dataset, demonstrating superior accuracy compared to existing models. The results highlight the potential of leveraging transfer learning and deep ensemble techniques...
SHIFT15M SHIFT15M: Fashion-specific dataset for set-to-set matching with several distribution shifts CVPRW 2023) paper code Japan BiHGH Bi-directional Heterogeneous Graph Hashing towards Efficient Outfit Recommendation MM 2022 paper - Australia OutfitTransformer OutfitTransformer: Outfit Representations for...
In this paper, we introduce Bangle Fashion Image Retrieval (BangleFIR), a novel dataset focusing on bangles within the fashion domain. While garment and fo
Thus, this study aims to build a Hybrid Style Framework to develop a fashion image dataset that can be efficiently applied to supervised learning. We conducted focus group interviews with six fashion experts to determine fashion style categories with which to classify hybrid styles in fashion images...
(C-MSAR) and parallel MSAR (P-MSAR). C-MSAR concatenates multiple sequence datasets in the input and then builds a recommendation model using combined input dataset, whereas P-MSAR builds a model with individual sequence datasets and aggregates the outputs of individual models by weighting them ...
Second, I will make a classification model that uses the review analysis to predict the recommendation/rating of a product. Data preprocessing Let's begin by importing the dataset. import pandas as pd import numpy as np df = pd.read_csv('./datasets/Womens Clothing E-Commerce Reviews.csv')...
[63, 62] proposed two approaches for en- hancing the text-image feature fusion by adding constraints, and using offline interactive recommendation. Recently, Yuan et al. [60] released the first multi-turn fashion image retrieval dataset, based on the original single...
The system consists of two main components: the YOLOv8 convolutional neural network trained on DeepFashion2 dataset, which detects and crops clothing items, and the GPT-4.0 large language model, which generates informative style commentary and recommendations. YOLOv8 is briefly trained on a specific ...
For the dataset please contact the original curators from this Paper Use Citation @misc{sagar2020paibpr, title={PAI-BPR: Personalized Outfit Recommendation Scheme with Attribute-wise Interpretability}, author={Dikshant Sagar and Jatin Garg and Prarthana Kansal and Sejal Bhalla and Rajiv Ratn Shah ...
with the system; IGA was used build the preferential model of users to tackle the personalization part of fashion style recommendation; By incorporating the psychological decision making model, Multi-alternative decision making (MDFT) model to be specific, into the final preferential set of IGA...