DEV Community: Voxel51

July 1 - Getting Started with FiftyOne Workshop

Jimmy Guerrero — Wed, 24 Jun 2026 19:09:56 +0000

In this session, you’ll learn how to manage large-scale computer vision datasets using the open source FiftyOne library and app.

Register for the Zoom!

We’ll cover how to curate, visualize, and evaluate your data and models — with a focus on improving data quality over brute-force model iteration.

You’ll walk away with a repeatable framework for building data-centric AI pipelines across research and production.

June 25 - AI, ML, and Computer Vision Meetup

Jimmy Guerrero — Mon, 22 Jun 2026 16:58:02 +0000

Join us on June 25 at 9 AM Pacific for the monthly AI, ML, and Computer Vision Meetup!

Register for the Zoom

Talks will include:

Large-Scale Scene Reconstruction via Local View Transformers - Tooba Imtiaz at Northeastern University
Enhancing Low-Field MRI with Deep Super-Resolution for Improved Nipah Virus Neuroimaging - Ajay Sharma at Johns Hopkins University
Lessons learned from running AI workloads in production - David Hughes at Stelia
And Now for Something Completely Different with FiftyOne - Burhan Qaddoumi at Voxel51

June 30 - Annotate the Right Data and Maximize Model Performance

Jimmy Guerrero — Thu, 18 Jun 2026 16:40:01 +0000

Join us for a hands-on virtual session on June 30 to learn how to build a complete physical AI data engine.

Register for the Zoom

In this workshop we’ll demonstrate workflows for image and video annotation, instance segmentation, polylines, QA and review, collaborative labeling operations in FiftyOne, and smart data selection strategies that help teams reduce wasted labeling spend.

June 25 - AI, ML, and Computer Vision Meetup

Jimmy Guerrero — Tue, 16 Jun 2026 16:19:59 +0000

Join us on June 25 for the monthly AI, ML, and Computer Vision Meetup!

Register for the Zoom

Talks will include:

Large-Scale Scene Reconstruction via Local View Transformers - Tooba Imtiaz at Northeastern University
Enhancing Low-Field MRI with Deep Super-Resolution for Improved Nipah Virus Neuroimaging - Ajay Sharma at Johns Hopkins University
Lessons learned from running AI workloads in production - David Hughes at Stelia
And Now for Something Completely Different with FiftyOne - Burhan Qaddoumi at Voxel51

June 17 - Build Vision Data Agents with Skills, and MCP

Jimmy Guerrero — Mon, 15 Jun 2026 16:43:27 +0000

Join us June 17 at 9 AM Pacific for a virtual workshop to learn how to build production-ready AI agents.

Register for the Zoom

Learn how to build production-ready AI agents that can reason over your data, automate complex tasks, and integrate seamlessly into your existing stack using tools, skills, and the Model Context Protocol (MCP).

June 17 - Build Vision Data Agents with Tools, Skills, and MCP

Jimmy Guerrero — Tue, 09 Jun 2026 18:09:18 +0000

Join us on June 17 for a virtual workshop to learn how to build production-ready AI agents. Register for the Zoom!

We’ll walk through how modern agentic systems move beyond simple prompts—leveraging structured tools like dataset operations, embeddings, evaluation pipelines, and model execution to take real action. You’ll see how these agents can tag data, run inference, evaluate performance, and surface insights automatically, all within a unified workflow.

By combining natural language interfaces with programmable building blocks, teams can dramatically reduce manual effort, accelerate experimentation, and unlock faster decision-making across the ML lifecycle.

June 9 - Visual AI in Healthcare: Ground Truth in the Foundation-Model Era

Jimmy Guerrero — Mon, 08 Jun 2026 20:46:41 +0000

Join us on June 9 for a virtual workshop to learn how to handle expert label disagreement and build high performing fine-tuned medical foundation models for clinical imaging tasks. Register for the Zoom!

Medical imaging teams are increasingly fine-tuning foundation models like UNI, MedSAM2, and BiomedCLIP on small in-house datasets. At that scale, label disagreement is a dominant cause of model failures, and the disputed ground truth is what regulators will ask you to defend. We'll build a medical imaging dataset in FiftyOne, surfacing and analyzing the cases where reviewers disagree. From there, we'll fine-tune a foundation model on cleaned data and use FiftyOne to evaluate where our model succeeds and fails, and which data is needed to move the model’s performance forward.

You’ll learn how to:

Build a medical imaging dataset that preserves multiple expert annotations as first-class fields
Use FiftyOne views, embedding similarity, and confidence-disagreement signals to find the samples where reviewers split.
Run label-quality screens, near-duplicate detection, and active-learning sample selection using foundation model embeddings
Fine-tune a medical foundation model on a defensible dataset, with auditable and versioned experiment tracking
Filter and slice evaluation for regulatory and clinical readiness
Drive the pipeline with natural-language agents using the FiftyOne MCP Server and Skills to run the same curation, evaluation, and review workflows from your favorite AI tool

June 9 - Visual AI in Healthcare: Ground Truth in the Foundation-Model Era

Jimmy Guerrero — Fri, 29 May 2026 15:13:57 +0000

Join us on June 9 for a virtual workshop to learn how to handle expert label disagreement and build high performing fine-tuned medical foundation models for clinical imaging tasks.

Register for the Zoom

You’ll learn how to:

Build a medical imaging dataset that preserves multiple expert annotations as first-class fields
Use FiftyOne views, embedding similarity, and confidence-disagreement signals to find the samples where reviewers split.
Run label-quality screens, near-duplicate detection, and active-learning sample selection using foundation model embeddings
Fine-tune a medical foundation model on a defensible dataset, with auditable and versioned experiment tracking
Filter and slice evaluation for regulatory and clinical readiness
Drive the pipeline with natural-language agents using the FiftyOne MCP Server and Skills to run the same curation, evaluation, and review workflows from your favorite AI tool

May 27 - Video Understanding Workshop

Jimmy Guerrero — Fri, 22 May 2026 16:12:02 +0000

Join us for a hands-on virtual session on May 27 exploring video-native multimodal AI and how to integrate cutting-edge video understanding models into your computer vision workflows.

Register for the Zoom

Akshat Shrivastava from Perceptron will introduce their latest video-native multimodal model that matches frontier models at a fraction of inference cost, followed by Harpreet Sahota demonstrating how to get started with Perceptron AI inside FiftyOne.

Work through annotation QA, large scale dataset curation, and model evaluation workflows with the Voxel51 team — customized to your use case, your tech stack, and your data. These hands-on workshops are delivered by FiftyOne experts, available through virtual and in-person formats.

Book a workshop!

See you online!

June 25 - AI, ML and Computer Vision Meetup

Jimmy Guerrero — Wed, 20 May 2026 16:47:09 +0000

Date, Time and Location

Jun 25, 2026
9AM Pacific
Online. Register for the Zoom!

Talks will include:

Large-Scale Scene Reconstruction via Local View Transformers

Transformer-based models have advanced 3D scene reconstruction, but their quadratic attention limits scalability to large scenes. We introduce the Local View Transformer (LVT), which replaces global attention with locality-aware attention over neighboring views, conditioned on relative camera geometry. LVT decodes directly into 3D Gaussian splats with view-dependent color and opacity for high-fidelity rendering. Our approach enables scalable, single-pass reconstruction of large, high-resolution scenes.

About the Speaker

Tooba Imtiaz is a PhD candidate in Electrical and Computer Engineering at Northeastern University, working in the Machine Learning Lab.

Lessons learned from running AI workloads in production

He’ll share his “tales from the engine room” - practical insights from operating AI systems at scale, including the challenges of abstraction layers, the realities of data movement and hardware constraints, and how systems thinking is essential for building high-performance, secure, and responsible AI infrastructure.

About the Speaker

Dave Hughes is CTO at Stelia. He was formerly CTO at Genesis Cloud, which pioneered what is now commonly known as 'neoclouds', and Principal Engineer/Interim Director of Engineering at Adjust GmbH where he built large-scale data warehousing and processing.

Enhancing Low-Field MRI with Deep Super-Resolution for Improved Nipah Virus Neuroimaging

Advances in deep learning make very-low-field (VLF) MRI systems a viable alternative for in vivo neuroimaging. Zero-shot super-resolution, self-supervised learning, and generative AI were explored to improve the quality of low-field MRI images. We present a framework for the first deployment of a VLF scanner for imaging Nipah virus-inoculated nonhuman primates (NHPs) using a 0.05 T MRI system.

First, a retrospective simulation study assessed the feasibility of imaging NiV infection at low field, followed by a prospective deployment (0.05 T) that enabled longitudinal imaging. The VLF-NiV imaging was characterized by low image quality and included multiple contrasts. A deep learning-based unpaired domain adaptation (CycleGAN) conditioned on acquisition parameters was used to harmonize contrast, and a simulation-based ResUNet model was used to reduce unwanted noise and preserve T2-weighted structural fidelity. We also highlight studies involving zero-shot super-resolution and denoising experiments that are advantageous for accessible neuroimaging.

About the Speaker

Ajay Sharma is a deep learning engineer with a broad background in biomedical image analysis. His research focuses on developing advanced deep learning methods for computer-aided disease detection and diagnosis.

And Now for Something Completely Different with FiftyOne

Often the best way to understand what a tool is truly capable of, is to use in ways it was never intended to be used. This session pushes FiftyOne past its computer vision roots through a series of demos showing how to push the boundaries with FiftyOne. A few practical, some playful, all built with open source code. You'll see how FiftyOne's core building blocks generalize far beyond labeled datasets, and leave with patterns and ideas you can take in your own direction.

About the Speaker

Burhan Qaddoumi is a ML DevRel Engineer at Voxel51 and perpetual "new guy" as a life long learner. Active in communities all across the web, eager to help, learn, and share with others that demonstrate initiative, interest, and drive.

May 1 - Best of WACV 2026

Jimmy Guerrero — Wed, 29 Apr 2026 16:07:22 +0000

Join us on May 1 for day two of the Best of WACV 2026 series of virtual events.

Register for the Zoom

Talks will include:

Beyond Pixels: Type-Aware Contrastive Learning for Global Urban Similarity - Idan Kligvasser at Google Research
Perceptually Guided 3DGS Streaming and Rendering for Mixed Reality - Sai Harsha Mupparaju at New York University
SAVIOR: Sample-efficient Adaptation of Vision-Language Models for OCR Representation - Akshata Bhat at Hyperbots Inc.
SynthForm: Towards a DLA-free E2E Form understanding model - Andre Fu at Ecliptor

April 30 - Best of WACV 2026 (Day 1)

Jimmy Guerrero — Tue, 28 Apr 2026 20:30:25 +0000

Join us on April 30 for day one of the Best of WACV 2026 series of virtual events.

Register for the Zoom!

Talks will include:

Zero-Shot Coreset Selection via Iterative Subspace Sampling - Brent Griffin at Voxel51
ENCORE: A Neural Collapse Perspective on Out-of-Distribution Detection in Deep Neural Networks - A Q M Sazzad Sayyed at Northeastern University
Synthesizing Compositional Videos from Text Description - Shanmuganathan Raman at IIT Gandhinagar
The Perceptual Observatory Characterizing Robustness and Grounding in MLLMs - Fenil Bardoliya at Arizona State University