An Introduction to YOLO26

yurimo•5 minutes ago

Wow I'm old, I still remember working with YOLOv2.

esquire_900•39 minutes ago

We've been running YOLO for a number of years (since v5) on soccer videos. None of the recent iterations have been significantly better, with v26 scoring worse then v9 and v11 on our tasks. Makes me wonder why this version is being pushed by roboflow and ultralytics.

teruakohatu•22 minutes ago

When I was working with YOLO models it did seem like any practical improvements were between all of the spinoff models. It seemed people were pushing new models for personal recognition since the original creator stopped working on it.

That said, many of the claimed improvements in this model were are efficiency related.

Onavo•29 minutes ago

The original YOLO author has long quit due to ethical reasons.

utopiah•10 minutes ago

Despite having a very memorable paper on the topic I believe they now work at Ai2.

speedgoose•20 minutes ago

I found that while CLIPSeg is slower than YOLOn, it is still pretty fast and if gave me much much better results without training.

If you want to detect objects and speed is important so you can’t use a LLM architecture, you can give it a try too.

Tepix•24 minutes ago

With some previous versions of YOLO I‘ve found pages that run it in real-time locally on your browser, analyzing the webcam.

Is there a demo like that available for YOLO26?

ktallett•about 1 hour ago

I am curious why there is no desire to produce a paper showcasing key details.

teleforce•16 minutes ago

Ultralytics YOLO26: Unified Real-Time End-to-End Vision Models:

https://arxiv.org/abs/2606.03748

m00dy•27 minutes ago

Ive used YOLO26 in one of my projects, It was very easy to train on our custom dataset and also very easy to deploy even on rust with AVX2 support. This model is indeed fast and can be used for almost real time inference.

An Introduction to YOLO26

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