In this paper, we present an open-set object detector, called Grounding DINO, by marrying
Transformer-based detector DINO with grounded pre-training, which can detect arbitrary …

Modern object detectors have achieved impressive progress under the close-set setup.
However, open-set object detection (OSOD) remains challenging since objects of unknown …

Recently, vision-language pre-training shows great potential in open-vocabulary object
detection, where detectors trained on base classes are devised for detecting new classes …

Open-world object detection, as a more general and challenging goal, aims to recognize
and localize objects described by arbitrary category names. The recent work GLIP …

Open-vocabulary object detection aims to detect novel object categories beyond the training
set. The advanced open-vocabulary two-stage detectors employ instance-level visual-to …

Zero-shot object detection aims at incorporating class semantic vectors to realize the
detection of (both seen and) unseen classes given an unconstrained test image. In this …

Zero-shot detection, namely, localizing both seen and unseen objects, increasingly gains
importance for large-scale applications, with large number of object classes, since …

The existing zero-shot detection approaches project visual features to the semantic domain
for seen objects, hoping to map unseen objects to their corresponding semantics during …

A more realistic object detection paradigm, Open-World Object Detection, has arisen
increasing research interests in the community recently. A qualified open-world object …

Zero-shot detection (ZSD) is crucial to large-scale object detection with the aim of
simultaneously localizing and recognizing unseen objects. There remain several challenges …