Computer Vision

12 Jan 2026 • 7 min read

How to Automate on Shelf Availability with Vision AI

In this tutorial, you’ll build a complete system that detects empty shelf facings, deploys a model in Roboflow, and turns every detection into an actionable Slack alert with shelf context and visual proof.

1 Jan 2026 • 20 min read

Getting Started with Roboflow

Roboflow eliminates boilerplate code when building object detection models. Get started with an example.

31 Dec 2025 • 7 min read

Small Defect Detection with Computer Vision

Detecting small, subtle defects is one of the hardest problems in computer vision, and one of the most common in the real world. Learn how to spot cracks, scratches, and surface damage using smart data collection, fast annotation with SAM3, and sliced inference with SAHI.

31 Dec 2025 • 10 min read

How to Grow Small Vision Datasets with SAM 3 and Synthetic Augmentation

Traditional image augmentation can make datasets bigger without making models better. In this tutorial, we show how to use SAM 3 to generate clean instance segmentation masks, apply segmentation-aware augmentation in Roboflow, and measure whether those changes actually improve model performance.

30 Dec 2025 • 11 min read

Vision Agents

This hands-on guide shows how to use Gemini 3 Pro and Roboflow Workflows to build Vision AI Agents.

29 Dec 2025 • 7 min read

Spatial Intelligence

As AI systems move beyond screens and into the physical world, understanding three-dimensional space becomes essential. This article explains spatial intelligence: how AI builds world models, reasons about depth and motion, and moves from recognizing images to acting reliably in real environments.

22 Dec 2025 • 4 min read

AI for Live Video: Introducing the Serverless Streaming API

Today we are announcing the Serverless Video Streaming API, the simplest way to run AI on live video streams. Previously, using AI to understand live video streams meant managing complex cloud infrastructure or configuring local hardware. The Serverless Video Streaming API removes those barriers, allowing you to run powerful vision

16 Dec 2025 • 6 min read

How to Monitor and Improve AI Models in Production

Learn how to monitor a model in production, and improve its performance.

11 Dec 2025 • 8 min read

Dock Door Utilization Tracking with Vision AI

Learn how to detect occupied vs. empty docks, read door numbers with OCR, and export clean JSON and CSV for real-world time and usage studies.

10 Dec 2025 • 14 min read

AI for Aerial Imagery: RF-DETR Delivers Best-in-Class Speed and Accuracy

Learn how models like RF-DETR deliver better accuracy when analyzing aerial imagery, and find out how computer vision is transforming operations across various sectors, including energy, industrial infrastructure, and defense.

10 Dec 2025 • 10 min read

How to Build a Vision App with Claude and Roboflow

Turn simple detections into intelligent, automated systems. Learn how to build a real-world vision workflow using Roboflow and Claude 4.5 Sonnet to track objects on a conveyor belt and store results in a live database.

9 Dec 2025 • 4 min read

Introducing Roboflow Rapid: Text prompt to vision model in minutes

For most of computer vision's history, training has been extremely challenging. Going from an idea to a deployed application meant spending weeks labeling hundreds or thousands of images by hand just to see if a concept would work. Now the era of manual labeling is ending. Today, we

8 Dec 2025 • 12 min read

Vision AI Camera Calibration Guide

Learn what camera calibration is, and see how to calibrate a camera step by step with Roboflow.

1 Dec 2025 • 12 min read

Vision Transformer vs. CNN for Object Detection

This guide explains how CNNs and ViTs differ, when to use each, and how to train and compare them directly inside Roboflow so you can choose the best architecture for your detection task.

1 Dec 2025 • 7 min read

No-Code Computer Vision Tools & Platforms: Beginner's Guide

Anyone can now build production-ready vision systems without writing a line of code. This guide breaks down the top no-code and low-code platforms, their strengths and tradeoffs, and how to choose the right one for your workflow.

25 Nov 2025 • 15 min read

Meta SAM 3D: Introduction

Understand what is SAM 3d and learn how to use SAM 3D + Roboflow to generate synthetic data and train a computer vision model.

19 Nov 2025 • 10 min read

What Is Promptable Concept Segmentation (PCS)?

Discover the concept of Promptable Concept Segmentation (PCS), how is it compares with other segmentation tasks such as semantic, instance, and panoptic, and the SAM 3 architecture, data and training infrastructure that makes PCS possible.

19 Nov 2025 • 8 min read

How to Fine-Tune Segment Anything 3 (SAM 3) on a Custom Dataset

Learn how to fine-tune SAM-3 for image segmentation with a custom dataset.

19 Nov 2025 • 5 min read

Launch: Use Segment Anything 3 (SAM 3) with Roboflow

Today, we are introducing new tools powered by Segment Anything 3 (SAM 3) that significantly change how people build computer vision applications. SAM 3 is a powerful vision foundation model that detects, segments, and tracks objects in images and videos based on prompts. See our detailed SAM 3 model overview

19 Nov 2025 • 12 min read

SAM 3: Segment Anything with Concepts

Learn what SAM 3 is, what you can do with the model, see examples of SAM 3 in use, and learn how you can use the model.

14 Nov 2025 • 9 min read

How to Train an RF-DETR Segmentation Model with a Custom Dataset

Learn how to train an RF-DETR Segmentation model with a custom dataset.

13 Nov 2025 • 3 min read

Roboflow Named Leader in Image Recognition Software

We’re proud to announce that as of November 2025, Roboflow has been ranked the #1 Image Recognition product on G2.

10 Nov 2025 • 9 min read

Best iOS Object Detection Models

Explore the best iOS object detection models: RF-DETR, YOLO11, and MobileNet SSD. Learn how to train, quantize, and deploy vision AI on iOS.

10 Nov 2025 • 13 min read

How Much Training Data Do You Need to Train a Computer Vision Model?

Discover how to find the right amount of training data for your computer vision project. Learn how dataset size, balance, and annotation quality impact model accuracy.