Omni-DETR: Omni-Supervised Object Detection with Transformers Pei Wang2,⋆ Zhaowei Cai1,† Hao Yang1 Gurumurthy Swaminathan1 Nuno Vasconcelos2 Bernt Schiele1 Stefano Soatto1 AWS AI Labs1 UC San Diego2 {zhaoweic,haoyng,gurumurs,bschiel,soattos}@amazon.com {pew062,...
Most of the existing object detection works are based on the bounding box annotation: each object has a precise annotated box. However, for rib fractures, the bounding box annotation is very labor-intensive and time-consuming because radiologists need to investigate and annotate the rib fractures ...
Also, they did not try the state-of-the-art CNN based object detection methods on their tasks and the datasets they use are not publicly available. In [36], kangaroo surveillance is proposed for the first time with a small dataset and DPM based method in a fully supervised setting. On ...
One of the most popular current methods in object detection is the R-CNN [5] and its variants [6], which consists of a region pro- posal part (RPP) and a region classification part. The state-of-the-art RPP uses 576 R. Huang et al. a sliding-window scheme [6] which is not ...
Clinical Task Definition.We evaluate the proposed method on structure detection in 3D fetal brain neurosonography: a complex task in a challenging imaging modality. A standard fetal 3D neurosonography examination requires identification and evaluation of several key brain anatomies; namely, the lateral ...
Existing work on object detection often relies on a single form of annotation: the model is trained using either accurate yet costly bounding boxes or cheaper but less expressive image-level tags. However, real-world annotations are often diverse in form, which challenges these existing works. In...