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Vancouver, Canada
Conference
CVPR 2023
June 18 - 22, 2023
Vancouver, Canada

Overview

The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. This year, CVPR will be single track such that everyone can attend everything. The focus will be on few selected plenary talks, scientific discussions at poster sessions and plenty of time for networking and socializing.

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Workshops

CVPR 2023 Workshop on Autonomous Driving
June 18
The CVPR 2023 Workshop on Autonomous Driving (WAD) aims to gather researchers and engineers from academia and industry to discuss the latest advances in perception for autonomous driving. In this full-day workshop, we will host speakers as well as technical benchmark challenges to present the current state of the art, limitations and future directions in the field - arguably one of the most promising applications of computer vision and artificial intelligence.

Amazon organizer: Li Li

Website: https://cvpr2023.wad.vision/
CVPR 2023 Workshop on Biometrics
June 18
CVPR 2023 Workshop on Biometrics
Robust partial fingerprint recognition
Yufei Zhang, Rui Zhao, Ziyi Zhao, Naveen Ramakrishnan, Manoj Aggarwal, Gérard Medioni, Qiang Ji
2023
Computer vision
CVPR 2023 Workshop on Computer Vision in Sports
Unknown date
SoccerNet 2023 tracking challenge - MOT4MOT Team technical report
Gal Shitrit, Ishay Be'ery, Ido Yerushalmy
2023
Computer vision
Homography based player identification in live sports
Yash Pandya, Kaustav Nandy, Shivam Agarwal
2023
Computer vision
CVPR 2023 Workshop on LatinX in Computer Vision (LXCV)
June 18
The workshop is a one-day event with invited speakers, oral presentations, and posters. The event brings together faculty, graduate students, research scientists, and engineers for an opportunity to connect and exchange ideas. There will be a panel discussion and a mentoring session to discuss current research trends and career choices in computer vision.

Website: https://www.latinxinai.org/cvpr-2023
Transfer learning for fine-grained classification using semi supervised learning and visual transformers
Manuel Lagunas Arto, Brayan Impata, Victor Martinez Gomez, Virginia Fernandez Arguedas, Christos Georgakis, Sofia Braun, Felipe Bertrand
2023
Computer vision
CVPR 2023 Workshop on Embodied AI
June 19
Minds live in bodies, and bodies move through a changing world. The goal of embodied artificial intelligence is to create agents, such as robots, which learn to creatively solve challenging tasks requiring interaction with the environment.

Amazon organizers: Govind Thattai and Xiaofeng Gao

Website: https://embodied-ai.org/
CVPR 2023 Workshop on 3D Scene Understanding for Vision, Graphics, and Robotics
June 18
The goal of this workshop is to foster interdisciplinary communication of researchers that are interested in addressing these challenges (computer vision, computer graphics, NLP, and robotics) so that more attention of the broader community can be drawn to this field. Through this workshop, current progress and future directions will be discussed, and new ideas and discoveries in related fields are expected to emerge.

Amazon organizer: Chuhang Zou

Website: https://scene-understanding.com/
CVPR 2023 Workshop on 3D Vision and Robotics (3DVR)
June 18
This workshop will provide a venue for people interested in 3D and robotics to come together to discuss the various challenges and problems in this area.

Amazon organizer: Erran Li

Website: https://sites.google.com/view/cvpr2023-3d-vision-robotics
CVPR 2023 Workshop on VAND: Visual Anomaly and Novelty Detection
June 18
Anomaly detection, and the synonymous topics of novelty and out-of-distribution detection, represent an important and application-relevant challenge within both computer vision and the broader field of pattern recognition. This workshop brings together researchers of both industry and academia to present and discuss recent developments, opportunities and open challenges in this area. The workshop will also host a challenge for zero-/few-normal-shot anomaly detection, to encourage the development and benchmarking new algorithms for realistic yet challenging tasks.

Amazon organizers: Thomas Brox, Latha Pemula, Yang Zou, Taewan Kim, and Onkar Dabeer

Website: https://sites.google.com/view/vand-cvpr23/home
CVPR 2023 Workshop on Continual Learning in Computer Vision
June 18
Renate: A library for real-world continual learning
Martin Wistuba, Martin Ferianc, Lukas Balles, Cédric Archambeau, Giovanni Zappella
2023
Computer vision

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US, MA, North Reading
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Principal Data Scientist, AWS Marketing Science
CA, BC, Vancouver
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Applied Scientist, Amazon Robotics (AR)
US, WA, Seattle
Are you excited about developing generative AI and foundation models to revolutionize automation, robotics and computer vision? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale. We are looking for scientists, engineers and program managers for a variety of roles. The Amazon Robotics software team is seeking a Applied Scientist to focus on large vision and manipulation machine learning models. This includes building multi-viewpoint and time-series computer vision systems. It includes using machine learning to drive hardware movement. It includes building large-scale models using data from many different tasks and scenes. This work spans from basic research such as cross domain training, to experimenting on prototype in the lab, to running wide-scale A/B tests on robots in our facilities. Key job responsibilities * Research vision - Where should we be focusing our efforts * Research delivery – Proving/dis-proving strategies in offline data or in the lab * Production studies - Insights from production data or ad-hoc experimentation. About the team This team invents and runs robots focused on grasping and packing items. These are typically 6-dof style robotic arms. Our work ranges from the long-term-research on basic science to deploying/supporting large production fleets handling billions of items per year. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA
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Data Scientist I, Workforce Intelligence PXT-Talent
US, VA, Arlington
Amazon’s mission is to be the most customer centric company in the world. The Workforce Staffing (WFS) organization is on the front line of that mission by hiring the hourly fulfillment associates who make that mission a reality. To drive the necessary growth and continued scale of Amazon’s associate needs within a constrained employment environment, Amazon has created the Workforce Intelligence (WFI) team. This team will (re)invent how Amazon attracts, communicates with, and ultimately hires its hourly associates. This team owns multi-layered research and program implementation to drive deep learning, process improvements, and strategic recommendations to global leadership. Are you passionate about data? Do you enjoy questioning the status quo? Do complex and difficult challenges excite you? If yes, this may be the team for you. The Data Scientist will be responsible for creating cutting edge algorithms, predictive and prescriptive models as well as required data models to facilitate WFS at-scale warehouse associate hiring. This role acts as an internal consultant to the marketing, biz ops and candidate experience teams covering responsibilities such as at-scale hiring process improvement, analyzing large scale candidate/associate data and being strategic to providing best candidate hiring experience to WFS warehouse associate candidates. We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA
Research Scientist, Special Projects
US, WA, Seattle
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US, CA, Sunnyvale
Are you passionate about solving unique customer-facing problem at Amazon scale? Are you excited by developing and productionizing machine learning, deep learning algorithms and leveraging tons of Amazon data to learn and infer customer shopping patterns? Do you enjoy working with a diverse set of engineers, machine learning scientists, product managers and user-experience designers? If so, you have found the right match! Virtual Try On (VTO) at Amazon Fashion & Fitness is looking for an exceptional Applied Scientist to join us to build our next generation virtual try on experience. Our goal is to help customers evaluate how products will fit and flatter their unique self before they ship, transforming customers' shopping into a personalized journey of inspiration, discovery, and evaluation. In this role, you will be responsible for building scalable computer vision and machine learning (CVML) models, and automating their application and expansion to power customer-facing features. Key job responsibilities - Tackle ambiguous problems in Computer Vision and Machine Learning, and drive full life-cycle of CV/ML projects. - Build Computer Vision, Machine Learning and Generative AI models, perform proof-of-concept, experiment, optimize, and deploy your models into production. - Investigate and solve exciting and difficult challenges in Image Generation, 3D Computer Vision, Generative AI, Image Understanding and Deep Learning. - Run A/B experiments, gather data, and perform statistical tests. - Lead development and productionalization of CV, ML, and Gen AI models and algorithms by working across teams. Deliver end to end. - Act as a mentor to other scientists on the team. We are open to hiring candidates to work out of one of the following locations: Sunnyvale, CA, USA
Applied Scientist, Amazon
US, CA, Sunnyvale
At Amazon Fashion, we are obsessed with making Amazon Fashion the most loved fashion destinations globally. We're searching for Computer Vision pioneers who are passionate about technology, innovation, and customer experience, and who are enthusiastic about making a lasting impact on the industry. You'll be working with talented scientists, engineers, and product managers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey and change the world of eCommerce forever Key job responsibilities As a Applied Scientist, you will be at the forefront to define, own and drive the science that span multiple machine learning models and enabling multiple product/engineering teams and organizations. You will partner with product management and technical leadership to identify opportunities to innovate customer facing experiences. You will identify new areas of investment and work to align product roadmaps to deliver on these opportunities. As a science leader, you will not only develop unique scientific solutions, but more importantly influence strategy and outcomes across different Amazon organizations such as Search, Personalization and more. This role is inherently cross-functional and requires a strong ability to communicate, influence and earn the trust of software engineers, technical and business leadership. We are open to hiring candidates to work out of one of the following locations: Sunnyvale, CA, USA
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