Visual Discovery at Pinterest
arXiv:1702.04680
Abstract
Over the past three years Pinterest has experimented with several visual search and recommendation services, including Related Pins (2014), Similar Looks (2015), Flashlight (2016) and Lens (2017). This paper presents an overview of our visual discovery engine powering these services, and shares the rationales behind our technical and product decisions such as the use of object detection and interactive user interfaces. We conclude that this visual discovery engine significantly improves engagement in both search and recommendation tasks.
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Cited by in corpus (6)
- Speed/accuracy trade-offs for modern convolutional object detectors
- Classification is a Strong Baseline for Deep Metric Learning
- Visual search over billions of aerial and satellite images
- Virtual ID Discovery from E-commerce Media at Alibaba: Exploiting Richness of User Click Behavior for Visual Search Relevance
- On Gradient Boosted Decision Trees and Neural Rankers: A Case-Study on Short-Video Recommendations at ShareChat
- Learning a Unified Embedding for Visual Search at Pinterest