What we’re about
🖖 This virtual group is for data scientists, machine learning engineers, and open source enthusiasts who want to expand their knowledge of computer vision and complementary technologies. Every month we’ll bring you two diverse speakers working at the cutting edge of computer vision.
- Are you interested in speaking at a future Meetup?
- Is your company interested in sponsoring a Meetup?
Contact the Meetup organizers!
This Meetup is sponsored by Voxel51, the lead maintainers of the open source FiftyOne computer vision toolset. To learn more about FiftyOne, visit the project page on GitHub: https://github.com/voxel51/fiftyone
📣 Past Speakers
* Sage Elliott at Union.ai
* Michael Wornow at Microsoft
* Argo Saakyan at Veryfi
* Justin Trugman at Softwaretesting.ai
* Johannes Flotzinger at Universität der Bundeswehr München
* Harpreet Sahota at Deci,ai
* Nora Gourmelon at Friedrich-Alexander-Universität Erlangen-Nürnberg
* Reid Pryzant at Microsoft
* David Mezzetti at NeuML
* Chaitanya Mitash at Amazon Robotics
* Fan Wang at Amazon Robotics
* Mani Nambi at Amazon Robotics
* Joy Timmermans at Secury360
* Eduardo Alvarez at Intel
* Minye Wu at KU Leuven
* Jizhizi Li at University of Sydney
* Raz Petel at SightX
* Karttikeya Mangalam at UC Berkeley
* Dolev Ofri-Amar at Weizmann Institute of Science
* Roushanak Rahmat, PhD
* Folefac Martins
* Zhixi Cai at Monash University
* Filip Haltmayer at Zilliz
* Stephanie Fu at MIT
* Shobhita Sundaram at MIT
* Netanel Tamir at Weizmann Institute of Science
* Glenn Jocher at Ultralytics
* Michal Geyer at Weizmann Institute of Science
* Narek Tumanya at Weizmann Institute of Science
* Jerome Pasquero at Sama
* Eric Zimmermann at Sama
* Victor Anton at Wildlife.ai
* Shashwat Srivastava at Opendoor
* Eugene Khvedchenia at Deci.ai
* Hila Chefer at Tel-Aviv University
* Zhuo Wu at Intel
* Chuan Guo at University of Alberta
* Dhruv Batra Meta & Georgia Tech
* Benjamin Lahner at MIT
* Jiajing Chen at Syracuse University
* Soumik Rakshit at Weights & Biases
* Jiajing Chen at Syracuse University
* Paula Ramos, PhD at Intel
* Vishal Rajput at Skybase
* Cameron Wolfe at Alegion/Rice University
* Julien Simon at Hugging Face
* Kris Kitani at Carnegie Mellon University
* Anna Kogan at OpenCV.ai
* Kacper Łukawski at Qdrant
* Sri Anumakonda
* Tarik Hammadou at NVIDIA
* Zain Hasan at Weaviate
* Jai Chopra at LanceDB
* Sven Dickinson at University of Toronto & Samsung
* Nalini Singh at MIT
📚 Resources
* YouTube Playlist of previous Meetups
* Recap blogs including Q&A and speaker resource links
Sponsors
See all
Voxel51Administration, promotion, giveaways and charitable contributions.
Voxel51Administration, promotion, giveaways and charitable contributions.- Voxel51Administration, promotion, giveaways and charitable contributions.
- Voxel51Administration, promotion, giveaways and charitable contributions.
- Voxel51Administration, promotion, giveaways and charitable contributions.
- Voxel51Administration, promotion, giveaways and charitable contributions.
Upcoming events (4)
See all- Network event25 attendees from 14 groups hostingDec 4 - Workshop: Getting Started with Computer Vision and FiftyOneLink visible for attendees
Register for the Zoom
https://voxel51.com/computer-vision-events/getting-started-with-fiftyone-workshop-dec-4-2024/
About the workshop
Want greater visibility into the quality of your computer vision datasets and models? Then join Harpreet Sahota, Hacker in Residence and Machine Learning Engineer at Voxel51, for this free 90-minute, hands-on workshop to learn how to leverage the open source FiftyOne computer vision toolset.
In the first part of the workshop we’ll cover:
- FiftyOne Basics (terms, architecture, installation, and general usage)
- An overview of useful workflows to explore, understand, and curate your data
- How FiftyOne represents and semantically slices unstructured computer vision data
The second half will be a hands-on introduction to FiftyOne, where you will learn how to:
- Load datasets from the FiftyOne Dataset Zoo
- Navigate the FiftyOne App
- Programmatically inspect attributes of a dataset
- Add new sample and custom attributes to a dataset
- Generate and evaluate model predictions
- Save insightful views into the data
Prerequisites are a working knowledge of Python and basic computer vision. All attendees will get access to the tutorials, videos, and code examples used in the workshop.
About the Instructor
Harpreet Sahota is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in RAG, Agents, and Multimodal AI.
- Network event56 attendees from 14 groups hostingDec 12 - AI, ML and Computer Vision MeetupLink visible for attendees
Register for the Zoom:
https://voxel51.com/computer-vision-events/ai-machine-learning-computer-vision-meetup-dec-12-2024/
How We Built CoTracker3: Simpler and Better Point Tracking by Pseudo-Labeling Real Videos
CoTracker3 is a state-of-the-art point tracking model that introduces significant improvements in tracking objects through video sequences. Its key innovations include:
- Uses semi-supervised training with real videos, reducing reliance on synthetic data1
- Generates pseudo-labels using existing tracking models as teachers1
- Features a simplified architecture compared to previous trackers
About the Speaker
Nikita Karaev is currently doing a PhD at Meta AI and Oxford, where he’s working on dynamic reconstruction and motion estimation (CoTracker) with Andrea Vedaldi and Christian Rupprecht. Before that, he did his master’s at École Polytechnique (Paris), and undergrad in cold Siberia (Novosibirsk). He was also an early employee at two startups that got acquired by Snapchat and Farfetch.
Hands-On with Meta AI's CoTracker3: Parsing and Visualizing Point Tracking Output
In this presentation, Harpreet Sahota explores CoTracker3, a state-of-the-art point tracking model that effectively leverages real-world videos during training. He dives into the practical aspects of running inference with CoTracker3 and parsing its output into FiftyOne, a powerful open-source tool for dataset curation, analysis, and visualization. Through a hands-on demonstration, Harpreet shows how to prepare a video for inference, run the model, examine its output, and parse the model’s output into FiftyOne’s keypoint format for seamless integration and visualization within the FiftyOne app.
About the Speaker
Harpreet Sahota is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in RAG, Agents, and Multimodal AI.
Streamlined Retail Product Detection with YOLOv8 and FiftyOne
In the fast-paced retail environment, automation at checkout is increasingly essential to enhance operational efficiency and improve the customer experience.
This talk will demonstrate a streamlined approach to retail product detection using the Retail Product Checkout (RPC) dataset, which includes 200 SKUs across 17 meta-categories such as puffed food, dried food, and drinks.
By leveraging YOLOv8, renowned for its speed and accuracy in real-time object detection, and FiftyOne, an open-source toolset for computer vision, we can simplify data loading, training, evaluation, and visualization for effective product detection and classification. Attendees will gain insights into how these tools can be applied to optimize checkout automation.
About the Speaker
Vanshika Jain is a Data Engineer Intern at UNAR Labs, a startup focused on making information accessible for the blind. She holds a Master’s degree in Machine Learning and Computer Vision from Northeastern University and is passionate about applying AI and computer vision to real-world problems, with a focus on automation and accessibility.
- Jan 16 - Ann Arbor AI, ML and Computer Vision MeetupThe Collaboration Space at UMTRI, Ann Arbor, MI
Date and Time
Jan 16, 2025 from 5:30 PM to 8:30 PMLocation
The Collaboration Space at UMTRI, 2901 Baxter Rd, Ann Arbor, MIMcity Data Engine: From Data Stream to AI Model
The Mcity data engine is designed to train AI models on large volumes of raw sensor data. For our current use case, data is collected from roadside fisheye cameras that capture traffic at intersections. FiftyOne is used to curate the data and select diverse samples for labeling. The labeled dataset is then used to train object detectors/trackers/predictors of vehicles, bicyclists, and pedestrians.
About the Speaker
Daniel Bogdoll is a visiting research scholar at Mcity and PhD student at Karlsruhe Institute of Technology, Germany. He has been working in the field of mobility for 9 years and currently focuses on detecting unusual scenarios.
Building Better Visual AI Datasets for Mobility
Building datasets for training visual AI models is laborious, error-prone, and expensive. Even worse, we lack the ability to measure how good a dataset is for a certain task. And, yet, we spend immense amounts of capital on building datasets, especially the case in the automotive sector. This talk will explore two vectors of inquiry around improving our ability to build measurably high-quality datasets for training models. First, I will explore discuss new methods in pruning large data-lakes down to size for model training guided by the ability to estimate dataset difficulty. Then, I will describe the potential for AI-human teaming when building and annotating datasets, leveraging a human in the loop to guide auto-labeling models when labeling complex scene geometry for mobility datasets.
About the Speaker
Dr. Jason Corso is a professor of electrical engineering and computer science at the University of Michigan and co-founder and CEO of Voxel51, an AI software company creating dev tools for improving the performance of computer vision and machine learning systems.
- Network event40 attendees from 16 groups hostingVisual AI for Geospatial DataLink visible for attendees
Date and Time
Jan 29, 2025 at 9 AM Pacific / Noon Eastern
Is AI Creating a Whole New Earth-Aware Geospatial Stack? Promises and Challenges
The latest wave of AI innovation is profoundly changing many domains. In remote sensing, despite efforts like ours at Clay and others, it is been less so. In this talk we will share our experience as we realize, and explore, if geoAI represents a whole new stack to work with Earth data.
About the Speaker
Dr. Bruno Sanchez-Andrade Nuno is the executive director of the non-profit project Clay, an AI model for remote sensing. Previously, Bruno has had more than a decace of operational geosptatial system like director of the Planetary Computer at Microsoft, Big Data innovations at the World Bank, and Chief Scientist at Mapbox.
Evaluating the Satlas and Clay Remote Sensing Foundational Models
Geospatial and Earth Observation have benefited from the new advances in computer vision. In this talk we are going to evaluate the accuracy and ease of use for two of these great new models – the Satlas and Clay foundational models. The evaluation will look at distinct different areas on the globe. Come see how this gift of foundational models improves your work in geospatial or Earth observation analysis.
About the Speaker
Steve Pousty is a dad, partner, son, a founder, and a principal developer advocate at Voxel51. He can teach you about Computer Vision, Data Analysis, Java, Python, PostgreSQL, Microservices, and Kubernetes. He has deep expertise in GIS/Spatial, Remote Sensing, Statistics, and Ecology. Steve has a Ph.D. in Ecology and can be bribed with offers of bird watching or fly fishing.
Earth Monitoring for Everyone with Earth Index
Earth Index is a end user focused application that preprocesses global imagery through AI foundation models to enable rapid in-browser search and monitoring. Earth Genome builds Earth Index for critical applications in the environment, and is being used today to report on illegal airstrips built in the Peruvian Amazon, track cattle factory farms across the planet for emissions modeling, and expose illegal gold mining in the Yanomami Indigenous Territory
About the Speaker
Mikel Maron works on open technology for the earth. He leads product development and sets organizational pace at Earth Genome. Previously, Mikel led corporate social responsibility at Mapbox, elevated open mapping in the federal government as a Presidential Innovation Fellow, and founded community mapping initiatives notably Map Kibera through Ground Truth Initiative. He has a long association with the OpenStreetMap project, founding Humanitarian OpenStreetMap Team in 2005 and serving many years on the OSM Foundation Board.
Past events (80)
See all- Network event22 attendees from 16 groups hostingECCV Redux: Day 4 - Nov 22This event has passed