Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines ...

This Collection showcases some of our latest research on computer vision, particularly highlighting the advance in recognition, classification, and segmentation.

Segmentation is a core task within computer vision that enables AI models to recognize objects they’re looking at in a given image. It’s used in a wide range of applications, from analyzing ...

Computer Vision (CV) has evolved rapidly in recent years and now permeates many areas of our daily life. To the average person, it might seem like a new and exciting innovation, but this isn’t ...

Computer vision is revolutioning the autonomy game - in movement automation, security, smart building monitoring, fraud detection and and traffic management. The power of semiconductors and AI are ...

Computer vision has some technical challenges as well. It’s limited by hardware, including cameras and sensors. Additionally, computer vision systems are very complex to scale.

Computer vision also depends on image segmentation. The process divides an image into different regions based on the characteristics of pixels to identify objects or boundaries to simplify an image ...

Meta AI Research open-sourced DINOv2, a foundation model for computer vision (CV) tasks. DINOv2 is pretrained on a curated dataset of 142M images and can be used as a backbone for several tasks, inclu ...

Computer vision systems are everywhere. They help classify and tag images on social media feeds, detect objects and faces in pictures and videos, and highlight relevant elements of an image.