141 citations · 209 across the 9 of their papers we have counts for
7 papers
Billion-Scale Pretraining with Vision Transformers for Multi-Task Visual Representations
Josh Beal, Hao-Yu Wu, Dong Huk Park +2
Large-scale pretraining of visual representations has led to state-of-the-art performance on a range of benchmark computer vision tasks, yet the benefits of these techniques at ext…
Toward Transformer-Based Object Detection
Josh Beal, Eric Kim, Eric Tzeng +3
Transformers have become the dominant model in natural language processing, owing to their ability to pretrain on massive amounts of data, then transfer to smaller, more specific t…
Bootstrapping Complete The Look at Pinterest
Eileen Li, Eric Kim, Andrew Zhai +2
Putting together an ideal outfit is a process that involves creativity and style intuition. This makes it a particularly difficult task to automate. Existing styling products gener…
Shop The Look: Building a Large Scale Visual Shopping System at Pinterest
Raymond Shiau, Hao-Yu Wu, Eric Kim +7
As online content becomes ever more visual, the demand for searching by visual queries grows correspondingly stronger. Shop The Look is an online shopping discovery service at Pint…
Learning a Unified Embedding for Visual Search at Pinterest
Andrew Zhai, Hao-Yu Wu, Eric Tzeng +2
At Pinterest, we utilize image embeddings throughout our search and recommendation systems to help our users navigate through visual content by powering experiences like browsing o…
Classification is a Strong Baseline for Deep Metric Learning
Andrew Zhai, Hao-Yu Wu
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…