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Specifically, we merge the quality estimation into the class prediction vector to form a joint representation of localization quality and classification, and use a vector to represent arbitrary distribution of box locations.
#13 best model for Object Detection on COCO test-dev
We train a standard object detector on a small, normally packed dataset with data augmentation techniques.
SOTA for Dense Object Detection on SKU-110K
We realize the framework for object detection and human pose estimation.
Our novel Focal Loss focuses training on a sparse set of hard examples and prevents the vast number of easy negatives from overwhelming the detector during training.
#3 best model for Dense Object Detection on SKU-110K