State-of-the-Art Object Detection with YOLO-NAS & FiftyOne
Learn how to work with the brand-new state-of-the-art object detection model YOLO-NAS in FiftyOne!
Category: Computer Vision
Generate Movement from Text Descriptions with T2M-GPT
Guest blogger Chien Vu explores T2M-GPT, including why it was created, how it works, and how to try it out!
Towards Controllable Diffusion Models with GLIGEN
Editor’s note: this is a guest post by Yuheng Li, computer science Ph.D. student at University of Wisconsin-Madison…
Automatically Set Up a New ML Project, Pain Free
Guest blogger Tarmily Wen of ADT describes how to use cookiecutter to automatically set up a new python ML project…
The Making of Avatar: The Way of Water
Learn how computer vision techniques like sensor fusion, performance capture, and frame interpolation made Avatar:…
Finding Images with Words
Learn how to add natural language image search to your computer vision pipelines with FiftyOne, Pinecone, and OpenAI’s…
Tunnel vision in computer vision: can ChatGPT see?
We pushed ChatGPT to its limits to see what it “knows” about computer vision. Check out the findings!
Why 2022 was the most exciting year in computer vision history (so far)
From AI-generated art to offsides detection in the World Cup, computer vision made a mark on 2022. Read this year’s…
Why FiftyOne is the pandas of Computer Vision
The pandas DataFrame & FiftyOne Dataset share similar functionalities. Learn how to use FiftyOne for computer vision…
On Notebooks and the Future of Computer Vision
Find out why notebooks have been great for CV/ML and what can still be learned from them.