CLIP is a gigantic leap forward, bringing many of the recent developments from the realm of natural language processing into the mainstream of computer vision: unsupervised learning, transformers, and multimodality
We've seen tremendous interest in Roboflow from the research community. Faculty and students from institutions ranging from California to Malta to Taiwan have been using Roboflow to accelerate their computer vision work.
Object detection research is white hot! In the last year alone, we've seen the state of the art reached by YOLOv4, YOLOv5, PP-YOLO, and Scaled-YOLOv4. And now Baidu releases PP-YOLOv2, setting new heights in the object detection space.
IBM recently announced they are shutting down IBM Visual Inspection, their product for creating custom computer vision models for classification and object detection. No new instances can be created and
Missed the event or looking for the recording? Check out the Roboflow + Paperspace Detectron2 webinar recording here and notebook here!Tomorrow, Roboflow and Paperspace are co-hosting a webinar teaching you
Excitement is building in the artificial intelligence community around MIT's recent release of liquid neural networks. The breakthroughs that Hasani and team have made are incredible. In this post, we will discuss the new liquid neural networks and what they might mean for the vision field.
Computer vision is a generational technology. Like the PC, internet, and mobile phones, computer vision’s impact will reshape every industry. In transportation, for example, the advent of machine vision