How to Use YOLO World for High-Performance Object Detection
Introduction
Imagine having a robot helper at home. Now picture the chaos after a long day — clothes scattered around, toys everywhere, and various objects out of place. How would this robot identify and organize each item, especially if it has never seen some of these objects before? Traditional object detectors would struggle with this task. Enter “YOLO World”, a revolutionary and new model in computer vision that promises to change how machines understand and interact with their surroundings.
YOLO-World is 20x faster and 5x smaller than leading zero-shot object detectors.
- Traditional Object Detectors (Faster R-CNN, SSD, YOLO) — small and fast but can only detect objects within a fixed set of categories defined by their training datasets
- Open-Vocabulary Object Detection (GLIP and Grounding DINO) — flexible but computationally intensive, requiring simultaneous encoding of images and texts for prediction
