Get to know the Amazon research community at CVPR 2018!

Amazon’s computer vision teams are looking forward to meeting you at CVPR 2018. Come and visit us at the Amazon booth, and read on for more information about academic collaboration, career opportunities, and our teams.

CVPR 2018 Publications

  • “Context Encoding for Semantic Segmentation” Authors: Hang Zhang (Rutgers University), Kristin Dana (Rutgers University), Jianping Shi (SenseTime), Zhongyue Zhang (Amazon), Xiaogang Wang (CUHK), Ambrish Tyagi (Amazon), Amit Agrawal (Amazon) Oral: Thursday 8:30-10:10 | Location: Ballroom
  • “Extreme 3D Face Reconstruction: Looking Past Occlusions” Authors: Anh Tran (USC), Tal Hassner (Open Univ. Israel, Amazon), Iacopo Masi (USC), Gérard Medioni (USC, Amazon)
  • “End-to-end Recovery of Human Shape and Pose” Authors: Angjoo Kanazawa (University of Maryland), Michael Black (Max Planck, Amazon), David Jacobs (University of Maryland), Jitendra Malik (UC Berkeley)
  • “Lions and Tigers and Bears: Capturing Non-Rigid, 3D, Articulated Shape from Images” Silvia Zuffi (IMATI-CNR), Angjoo Kanazawa (University of Maryland), Michael Black (Max Planck, Amazon)
  • “Compressed Video Action Recognition” Authors: Chao-Yuan Wu (UT Austin), Manzil Zaheer (Carnegie Mellon University), Hexiang Hu (USC) R. Manmatha (Amazon), Alexander Smola (Amazon), Philipp Krahenbuhl (UT Austin)
  • “Visual Relationship Learning with a Factorization-based Prior” Authors: Seong Jae Hwang (UW-Madison), Zirui Tao (UW-Madison), Vikas Singh (UW-Madison), Hyunwoo Kim (Amazon), Sathya Ravi (UW-Madison), Maxwell Collins (UW-Madison)
  • “Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination” Authors: Zhirong Wu (UC Berkeley), Yuanjun Xiong (Amazon), Stella Yu (UC Berkeley, ICSI), Dahua Lin (CUHK)
  • “Recognize Actions by Disentangling Components of Dynamics” Authors: Yue Zhao (CUHK), Yuanjun Xiong (Amazon), Dahua Lin (CUHK)
  • “Objects as context for detecting their semantic parts” Authors: Abel Gonzalez-Garcia (Univ. of Edinburgh), Davide Modolo (Amazon), Vitto Ferrari (Univ. of Edinburgh, Google)
  • “Optimizing Video Object Detection via a Scale-Time Lattice” Authors: Kai Chen (CUHK), Jiaqi Wang (CUHK), Shuo Yang (CUHK, Amazon), Xingcheng Zhang (CUHK), Yuanjun Xiong (CUHK, Amazon), Chen-Change Loy (CUHK), Dahua Lin (CUHK)
  • "Learning a Complete Image Indexing Pipeline" Authors: Himalaya Jain (Technicolor, INRIA), Joaquin Zepeda (Amazon), Patrick Pérez (Technicolor), Rémi Gribonval (INRIA)

Internships for PhD Students

We offer internships year-round, with opportunities in Seattle, San Francisco, Sunnyvale, Palo Alto, Cupertino, New York, Boston, Pittsburgh, Cambridge (UK) and Aachen and Berlin (DE). To apply, email your resume to CVPR2018@amazon.com. 

Job Opportunities for Graduating Students and Experienced Researchers

We are looking for results-driven individuals who apply advanced computer vision and machine learning techniques, love to work with data, are deeply technical, and highly innovative. If you long for the opportunity to invent and build solutions to challenging problems that directly impact the way Amazon transforms the consumer experience, we are the place for you. To apply, email your resume to CVPR2018@amazon.com and let us know if there are any specific locations, teams, or research leaders that you are interested in working with. 

Amazon Scholars

Amazon Scholars is a new program for academic leaders to work with Amazon in a flexible capacity, ranging from part-time to full-time research roles. Learn more at amazon.jobs/scholars.

Amazon Web Services (AWS) Research Grants

In partnership with Machine Learning@Amazon, AWS offers up to $20,000 in compute tokens each quarter to professors and students. Academics have used these grants for projects ranging from Hack End weekends to massive MRI imaging projects. AWS provides building blocks for developing applications ranging from Elastic MapReduce for Hadoop analytics to fast and scalable storage with Amazon DynamoDB. Learn more & apply here.
 
Amazon Research Awards

ARA is an unrestricted gift to recognize exceptional faculty, and fund projects leading toward a PhD degree or conducted as a part of post-doctoral work. Each selected proposal is assigned an Amazon research contact, as we believe that both sides benefit from direct interaction on the topic of their research. We invite ARA recipients to visit Amazon offices worldwide to give talks related to their work and meet with our research groups face-to-face. We encourage ARA recipients to publish the outcome of the project and commit any related code to open source code repositories. Learn more here.

Publishing at Amazon

Amazon is committed to innovating at the frontiers of machine learning and artificial intelligence. Our scientists are encouraged to engage in the research community in the form of written publications, open source code and public datasets. We have instituted a new, fast-track publication approval process, to help share our research efforts as quickly as possible, while maintaining the highest standards of quality.

Diversity at Amazon

We are a company of builders working on behalf of a global customer base. Diversity is core to our leadership principles, as we seek diverse perspectives so that we can be “Right, A Lot”. We welcome people from all backgrounds and perspectives to innovate with us. Learn more at amazon.com/diversity.

Learn more about Computer Vision teams and products at Amazon.

Amazon Go

Amazon Go is a new kind of store featuring the world’s most advanced shopping technology. No lines, no checkout – just grab and go!

Echo Look

“Alexa, take a photo.” Introducing Echo Look—hands-free camera and style assistant.

Amazon Rekognition - Deep Learning-Based Image Analysis

AWS Webinar: Amazon Rekognition is a service that makes it easy to add image analysis to your applications.

Prime Air

We're excited about Prime Air, a delivery system designed to safely get packages to customers in 30 minutes or less using drones.

Core AI

Amazon has developed an automated system that uses machine learning to determine the maturity of fruits and vegetables.

Augmented Reality

AR view lets you visualize products in your home, before you buy them. Visit amazon.com/adlp/arview to learn more.

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