Simple Summary Termites are structurally destructive pests that can infest a consumer's
most important investment, their home. The evolution of termite control is complex, involving …

In this paper, we introduce a large scale multi-objective ranking system for recommending
what video to watch next on an industrial video sharing platform. The system faces many …

The goal of this paper is to serve as a guide for selecting a detection architecture that
achieves the right speed/memory/accuracy balance for a given application and platform. To …

Deep metric learning aims to learn a function mapping image pixels to embedding feature
vectors that model the similarity between images. Two major applications of metric learning …

Labeling training data is one of the most costly bottlenecks in developing machine learning-
based applications. We present a first-of-its-kind study showing how existing knowledge …

Related Pins is the Web-scale recommender system that powers over 40% of user
engagement on Pinterest. This paper is a longitudinal study of three years of its …

Modeling fashion compatibility is challenging due to its complexity and subjectivity. Existing
work focuses on predicting compatibility between product images (eg an image containing a …

In this paper, we introduce a web-scale general visual search system deployed in Microsoft
Bing. The system accommodates tens of billions of images in the index, with thousands of …

At Pinterest, we utilize image embeddings throughout our search and recommendation
systems to help our users navigate through visual content by powering experiences like …

Our interviews with people who have visual impairments show clothes shopping is an
important activity in their lives. Unfortunately, clothes shopping web sites remain largely …