NeurBench is a benchmark suite that quantifies drift via a drift factor and generates data/workloads to evaluate learned database components under controllable drift scenarios.
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GeCo uses a cGAN-based Complementary Item Generation Model to create target fashion images from seed items and feeds them into a compatibility model for better top-bottom retrieval on three datasets, plus releases a new Fashion Taobao dataset.
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NeurBench: A Benchmark Suite for Learned Database Components with Drift Modeling
NeurBench is a benchmark suite that quantifies drift via a drift factor and generates data/workloads to evaluate learned database components under controllable drift scenarios.
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Fashion Image-to-Image Translation for Complementary Item Retrieval
GeCo uses a cGAN-based Complementary Item Generation Model to create target fashion images from seed items and feeds them into a compatibility model for better top-bottom retrieval on three datasets, plus releases a new Fashion Taobao dataset.