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 allUpcoming events (4+)
See all- Network event26 attendees from 14 groups hostingOct 30 - 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-oct-30-2024/
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 event21 attendees from 14 groups hostingNov 6 - Workshop: Developing Data-Centric AI Apps with FiftyOne PluginsLink visible for attendees
Register for the Zoom:
https://voxel51.com/computer-vision-events/developing-fiftyone-plugins-workshop-nov-6-2024/
Are you ready to take your computer vision tooling to the next level? Open source FiftyOne is the most flexible computer vision toolkit on the planet. By tapping into its built-in FiftyOne Plugin framework, you can extend your FiftyOne experience and streamline your workflows, building Gradio-like applications with data at their core.
From concept interpolation to image deduplication, optical character recognition, and even curating your own AI art gallery by adding generated images directly into a dataset, your imagination is the only limit. Join us to discover how you can unleash your creativity and interact with data like never before.
The FREE workshop will cover:
- FiftyOne Plugins – what are they?
- Installing a plugin
- Creating your own Python plugin
- Curate your own AI art gallery with DALLE3, SDXL, and Latent Consistency Models
- Bring GPT4 Vision directly to your data
- Run OCR, semantic document searches, and make your textual data visual
- Create an open-vocabulary labeling interface
Prerequisites
A working knowledge of Python and basic familiarity with FiftyOne. All attendees will get access to the tutorials, videos, and code examples used in the workshop.
About the Instructor
Daniel Gural is a seasoned Machine Learning Evangelist with a strong passion for empowering Data Scientists and ML Engineers to unlock the full potential of their data. Currently serving as a valuable member of Voxel51, he takes a leading role in efforts to bridge the gap between practitioners and the necessary tools, enabling them to achieve exceptional outcomes.
- Network event35 attendees from 14 groups hostingNov 14 - 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-nov-14-2024/
Human-in-the-loop: Practical Lessons for Building Comprehensive AI Systems
AI systems often struggle with data limitations, data distribution shift over time, and a poor user experience. Human-in-the-loop design offers a solution by placing users at the center of AI systems and leveraging human feedback for continuous improvement.
In this talk, we'll dive deeply into a recent project at Merantix Momentum: A interactive tool for automatic rodent behaviour analysis in videos at a large scale. We'll discuss the machine learning components, including pose estimation, behavior classification, and active learning and talk about the technical challenges and the impact of the project.
About the Speaker
Adrian Loy has a Msc in IT Systems Engineering and spent the last 5 years at Merantix Momentum planning and executing Computer Vision Projects for a variety of clients. He is currently leading the Machine Learning Engineering Team at Momentum.
Deploying ML models on Edge Devices using Qualcomm AI Hub
In this talk we address the common challenges faced by developers migrating AI workloads from the cloud to edge devices. Qualcomm aims to democratize AI at the edge, easing the transition to the edge by supporting familiar frameworks and data types. This is where Qualcomm AI Hub comes in. Developers can follow along, gaining knowledge and tools to efficiently deploy optimized models on real devices using Qualcomm AI Hub.
We’ll walk through how to get started using Qualcomm AI Hub, go through examples on how to optimize models and bundle the downloadable target asset into your application and talk through iterating on your model and meet performance requirements to deploy on device!
About the Speaker
Bhushan Sonawane has optimized and deployed more than 1000s of AI models on-device on iOS and Android ecosystem. Currently, he is building AI Hub at Qualcomm to make on-device journey on Android and Snapdragon platform as seamless as possible.
Curating Excellence: Strategies for Optimizing Visual AI Datasets
In this talk Harpreet will discuss common challenges plaguing visual AI datasets, their impact on model performance, and share some tips and tricks for curating datasets to make the most of any compute budget or network architecture.
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.
- Network event47 attendees from 16 groups hostingECCV Redux: Day 1 - Nov 19Link visible for attendees
Missed the European Conference on Computer Vision (ECCV) last month? Have no fear, we have collected some of the best research from the show into a series of online events.
Fast and Photo-realistic Novel View Synthesis from Sparse Images
Novel view synthesis generates new perspectives of a scene from a set of 2D images, enabling 3D applications like VR/AR, robotics, and autonomous driving. Current state-of-the-art methods produce high-fidelity results but require a lot of images, while sparse-view approaches often suffer from artifacts or slow inference. In this talk, I will present my research work focused on developing fast and photorealistic novel view synthesis techniques capable of handling extremely sparse input views.
ECCV 2024 Paper: CoherentGS: Sparse Novel View Synthesis with Coherent 3D Gaussians
About the Speaker
Avinash Paliwal is a PhD Candidate in the Aggie Graphics Group at Texas A&M University. His research is focused on 3D Computer Vision and Computational Photography.
Robust Calibration of Large Vision-Language Adapters
We empirically demonstrate that popular CLIP adaptation approaches, such as Adapters, Prompt Learning, and Test-Time Adaptation, substantially degrade the calibration capabilities of the zero-shot baseline in the presence of distributional drift. We identify the increase in logit ranges as the underlying cause of miscalibration of CLIP adaptation methods, contrasting with previous work on calibrating fully-supervised models. Motivated by these observations, we present a simple and model-agnostic solution to mitigate miscalibration, by scaling the logit range of each sample to its zero-shot prediction logits
ECCV 2024 Paper: Robust Calibration of Large Vision-Language Adapters
About the Speaker
Balamurali Murugesan is currently pursuing his Ph.D. in developing reliable deep learning models. Earlier, he completed his master’s thesis on accelerating MRI reconstruction. He has published 25+ research articles in renowned venues.
Tree-of-Life Meets AI: Knowledge-guided Generative Models for Understanding Species Evolution
A central challenge in biology is understanding how organisms evolve and adapt to their environment, acquiring variations in observable traits across the tree of life. However, measuring these traits is often subjective and labor-intensive, making trait discovery a highly label-scarce problem. With the advent of large-scale biological image repositories and advances in generative modeling, there is now an opportunity to accelerate the discovery of evolutionary traits. This talk focuses on using generative models to visualize evolutionary changes directly from images without relying on trait labels.
ECCV 2024 Paper: Hierarchical Conditioning of Diffusion Models Using Tree-of-Life for Studying Species Evolution
About the Speaker
Mridul Khurana is a PhD student at Virginia Tech and a researcher with the NSF Imageomics Institute. His research focuses on AI4Science, leveraging multimodal generative modeling to drive discoveries across scientific domains.
Past events (77)
See all- Network event160 attendees from 16 groups hostingOct 24 - AI, Machine Learning and Computer Vision MeetupThis event has passed