Abstract: Open-set object detection (OSOD) is an important research direction in computer vision, focusing on enhancing a model’s ability to detect unknown categories. Current methods are overly ...

We propose MaskCut approach to generate pseudo-masks for multiple objects in an image. CutLER can learn unsupervised object detectors and instance segmentors solely on ImageNet-1K. CutLER exhibits ...

RF-DETR is a real-time transformer architecture for object detection, instance segmentation, and keypoint detection (preview) developed by Roboflow. Built on a DINOv2 vision transformer backbone, ...

President Trump has delivered the same retort to political allies who have offered him strategic advice in recent weeks, according to people with knowledge of the conversations: “I’m the president and ...

Abstract: In real-world applications, detectors are expected to evolve and improve their perceptual abilities through incremental learning of the unknown. Open world object detection (OWOD) simulates ...