Computer Vision Reads

Thousands of people. Hundreds of cameras. One question: Can technology identify you in a crowd? Continue reading on Medium »

Learn how to build an object detection system that locates and classifies dice using CNN-based feature extraction, bounding box regression… Continue reading on

Learn how to build an object detection system that locates and classifies dice using CNN-based feature extraction, bounding box regression… Continue reading on

Building measurable spatial intelligence from monocular video with Depth Anything 3, SAM 3, calibrated cameras, and deterministic geometry Continue reading on M

What Vision AI taught me about speed, latency, benchmarking, and why model performance depends on more than the model. Continue reading on Women in Technology »

This is the first blog in an upcoming series documenting the build of a computer vision project — from raw data to a complete webapp… Continue reading on Toward

This is the first blog in an upcoming series documenting the build of a computer vision project — from raw data to a complete webapp… Continue reading on Toward

By Susanta Banik | Full-Stack AI Engineer & Deep-Tech Researcher 1. The Critical...

Artificial Intelligence is no longer just about recognizing objects — it’s about understanding movement, behavior, and interaction. Continue reading on Medium »

In 2019, my final-year project partner, Ayesha Alhashemi, and I worked together to build a robot for our Bachelor of Software Engineering… Continue reading on M

A daily deep dive into cv topics, coding problems, and platform features from PixelBank . Topic Deep Dive: Multi-View Stereo From the Depth Estimation chapter I

Human Eyes Miss Things. Computer Vision Doesn't Get Tired. Quality inspection is one of the most cognitively demanding jobs in manufacturing. An inspector exami

Picture a coach standing on the sideline, watching a match from one specific angle. Now picture a drone hovering directly overhead… Continue reading on Medium »

A portrait outline effect looks simple: find a person and draw a line around them. In real video, however, the problem quickly expands into subject identity, fi

arXiv:2607.24810v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong performance on general remote sensing tasks. However, their c

this fascinating analysis of facial processing deficits underscores a fundamental truth that many developers in the computer vision (CV) space overlook: "facial

When sharing screenshots in issue trackers, Slack channels, or public documentation, developers...

“YOLO finds the object, while OCR reads the text on it. Powerful on their own, these two technologies become the foundation of intelligent… Continue reading on

Why I felt like cheating feeding raw 3D points into a neural net until I understood the math behind it. Continue reading on Medium »

Why I felt like cheating feeding raw 3D points into a neural net until I understood the math behind it. Continue reading on Medium »

The hidden layers of modern identity verification For developers building in the computer vision or biometrics space, a simple face-match algorithm is no longer

I used to think computer vision was a model problem. It is a pipeline problem, and the model is the...

arXiv:2607.21617v1 Announce Type: new Abstract: Vision Language Models (VLMs) are increasingly used in place of traditional OCR pipelines for document understan

arXiv:2607.21628v1 Announce Type: new Abstract: Simulation-to-reality translation must bridge the appearance gap between synthetic and real domains while preser