![]() Than 4\% on average without seeing any corresponding images. Generalization ability on large-vocabulary datasets like LVIS, ImageNetBoxes,Īnd VisualGenome - it surpasses the traditional supervised baselines by more Our UniDetector behaves the strong zero-shot These contributions allow UniDetector to detect over 7kĬategories, the largest measurable category size so far, with only about 500Ĭlasses participating in training. 3) it further promotes the generalization ability to novelĬategories through our proposed decoupling training manner and probabilityĬalibration. Seen and unseen classes, thanks to abundant information from both vision and ![]() Spaces, which guarantees sufficient information for universal representations.Ģ) it generalizes to the open world easily while keeping the balance between Heterogeneous label spaces for training through the alignment of image and text Universality of UniDetector are: 1) it leverages images of multiple sources and Recognize enormous categories in the open world. Propose UniDetector, a universal object detector that has the ability to Open world severely restrict the universality of traditional detectors. ![]() The dependence on humanĪnnotations, the limited visual information, and the novel categories in the ![]() Download a PDF of the paper titled Detecting Everything in the Open World: Towards Universal Object Detection, by Zhenyu Wang and 6 other authors Download PDF Abstract: In this paper, we formally address universal object detection, which aims toĭetect every scene and predict every category. ![]()
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