Training-free framework that converts SAM3 into a real-time multi-class open-vocabulary detector. Achieves 55.8 AP on COCO val2017 (80 classes) at 15.8 FPS (4 classes, 1008px) on a single RTX 4080.
Abstract: YOLOv10, known for its efficiency in object detection methods, quickly and accurately detects objects in images. However, when detecting small objects in remote sensing imagery, traditional ...
Abstract: Open-vocabulary object detection (OVOD) aims to detect the objects beyond the set of classes observed during training. This work introduces a straightforward and efficient strategy that ...
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