English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Open world object detection aims at detecting objects that are absent in theobject classes of the training data as unknown objects without explicitsupervision. Furthermore, the exact classes of the unknown objects must beidentified without catastrophic forgetting of the previous known classes whenthe corresponding annotations of unknown objects are given incrementally. Inthis paper, we propose a two-stage training approach named Open World DETR foropen world object detection based on Deformable DETR. In the first stage, wepre-train a model on the current annotated data to detect objects from thecurrent known classes, and concurrently train an additional binary classifierto classify predictions into foreground or background classes. This helps themodel to build an unbiased feature representations that can facilitate thedetection of unknown classes in subsequent process. In the second stage, wefine-tune the class-specific components of the model with a multi-viewself-labeling strategy and a consistency constraint. Furthermore, we alleviatecatastrophic forgetting when the annotations of the unknown classes becomesavailable incrementally by using knowledge distillation and exemplar replay.Experimental results on PASCAL VOC and MS-COCO show that our proposed methodoutperforms other state-of-the-art open world object detection methods by alarge margin.

Open World DETR: Transformer based Open World Object Detection