… energy based unknown identification to address the challenges of open world detection. •
… helps to measure the open world characteristics of an object detector, and benchmark ORE …

… detector can directly perform inference in the open world. … , the trained detector will be biased
toward base categories. As … and hurt the detector’s performance in the open world. To avoid …

… and unknown object recognition. In recent times, there has been a notable surge in the
adaptation of transformer-based techniques in the context of Open World Object Detection (OW-…

… steps towards the problem of open world recognition. The key … rose to prominence in for
object recognition applications [46… [45] extended the approach to object recognition and …

… object detection. Open world object detection (OWOD) is an emerging area of research that
adapts this principle to explore new knowledge. It focuses on recognizing and learning from …

… framework, OW-DETR, for open-world object detection. The proposed OW-DETR comprises
… Faster r-cnn: Towards real-time object detection with region proposal networks. In NeurIPS, …

… open-world detector, PROB, integrates our framework into traditional object detection models,
adapting them for the open-world … Towards open world object detection. In Proceedings of …

… In this paper, we formulate the open-world 3D object detection task for autonomous driving.
To achieve openworld objectives, we propose OW3Det, which comprises a base detector, a …

… unseen objects. Our method is comprehensively evaluated on open world and incremental
object detection benchmarks, … Detecting everything in the open world: Towards universal …

… and practicality of object detection methods in open world remote sensing scenarios, this
paper proposes a method for detecting potential oriented objects in an open world setting. By …