Search Results for author: Andrew Zhai

Found 10 papers, 2 papers with code

PinnerFormer: Sequence Modeling for User Representation at Pinterest

no code implementations9 May 2022 Nikil Pancha, Andrew Zhai, Jure Leskovec, Charles Rosenberg

Sequential models have become increasingly popular in powering personalized recommendation systems over the past several years.

Recommendation Systems

Billion-Scale Pretraining with Vision Transformers for Multi-Task Visual Representations

no code implementations12 Aug 2021 Josh Beal, Hao-Yu Wu, Dong Huk Park, Andrew Zhai, Dmitry Kislyuk

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 extreme scale in complex production systems has been relatively unexplored.

Multi-Task Learning Representation Learning

Toward Transformer-Based Object Detection

no code implementations17 Dec 2020 Josh Beal, Eric Kim, Eric Tzeng, Dong Huk Park, Andrew Zhai, Dmitry Kislyuk

The Vision Transformer was the first major attempt to apply a pure transformer model directly to images as input, demonstrating that as compared to convolutional networks, transformer-based architectures can achieve competitive results on benchmark classification tasks.

Object Detection

Shop The Look: Building a Large Scale Visual Shopping System at Pinterest

no code implementations18 Jun 2020 Raymond Shiau, Hao-Yu Wu, Eric Kim, Yue Li Du, Anqi Guo, Zhiyuan Zhang, Eileen Li, Kunlong Gu, Charles Rosenberg, Andrew Zhai

As online content becomes ever more visual, the demand for searching by visual queries grows correspondingly stronger.

Object Detection

Bootstrapping Complete The Look at Pinterest

1 code implementation18 Jun 2020 Eileen Li, Eric Kim, Andrew Zhai, Josh Beal, Kunlong Gu

In this paper, we will describe how we bootstrapped the Complete The Look (CTL) system at Pinterest.

Learning a Unified Embedding for Visual Search at Pinterest

no code implementations5 Aug 2019 Andrew Zhai, Hao-Yu Wu, Eric Tzeng, Dong Huk Park, Charles Rosenberg

The solution we present not only allows us to train for multiple application objectives in a single deep neural network architecture, but takes advantage of correlated information in the combination of all training data from each application to generate a unified embedding that outperforms all specialized embeddings previously deployed for each product.

Metric Learning Recommendation Systems

Classification is a Strong Baseline for Deep Metric Learning

2 code implementations30 Nov 2018 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.

Binarization Classification +4

Visual Discovery at Pinterest

no code implementations15 Feb 2017 Andrew Zhai, Dmitry Kislyuk, Yushi Jing, Michael Feng, Eric Tzeng, Jeff Donahue, Yue Li Du, Trevor Darrell

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).

Object Detection

Visual Search at Pinterest

no code implementations28 May 2015 Yushi Jing, David Liu, Dmitry Kislyuk, Andrew Zhai, Jiajing Xu, Jeff Donahue, Sarah Tavel

We demonstrate that, with the availability of distributed computation platforms such as Amazon Web Services and open-source tools, it is possible for a small engineering team to build, launch and maintain a cost-effective, large-scale visual search system with widely available tools.

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