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Found 6 papers, 2 papers with code
Effective Transfer of Pretrained Large Visual Model for Fabric Defect Segmentation via Specifc Knowledge Injection
Fabric defect segmentation is integral to textile quality control.
OTFace: Hard Samples Guided Optimal Transport Loss for Deep Face Representation
To this end, some deep convolutional neural networks (CNNs) have been developed to learn discriminative feature by designing properly margin-based losses, which perform well on easy samples but fail on hard samples.
Reproducibility Companion Paper: Knowledge Enhanced Neural Fashion Trend Forecasting
This companion paper supports the replication of the fashion trend forecasting experiments with the KERN (Knowledge Enhanced Recurrent Network) method that we presented in the ICMR 2020.
Leveraging Two Types of Global Graph for Sequential Fashion Recommendation
Sequential fashion recommendation is of great significance in online fashion shopping, which accounts for an increasing portion of either fashion retailing or online e-commerce.
Leveraging Multiple Relations for Fashion Trend Forecasting Based on Social Media
Towards insightful fashion trend forecasting, previous work [1] proposed to analyze more fine-grained fashion elements which can informatively reveal fashion trends.
Knowledge Enhanced Neural Fashion Trend Forecasting
Further-more, to effectively model the time series data of fashion elements with rather complex patterns, we propose a Knowledge EnhancedRecurrent Network model (KERN) which takes advantage of the capability of deep recurrent neural networks in modeling time-series data.
