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Improve object detection using object co-occurrence statistics with GPR

Improve object detection using object co-occurrence statistics with GPR


Detecting Objects with Graph Priors and Graph Refinement

arXiv paper abstract https://arxiv.org/abs/2212.12395



... goal ... is to detect objects by exploiting their interrelationships.


Rather than relying on predefined and labeled graph structures, ... infer a graph prior from object co-occurrence statistics.


... idea ... is to model object relations as a function of initial class predictions and co-occurrence priors to generate a graph representation of an image for improved classification and bounding box regression.


... additionally learn the object-relation joint distribution ... Sampling from this distribution generates a refined graph representation of the image which in turn produces improved detection performance.


... demonstrate ... method is detector agnostic, end-to-end trainable, and especially beneficial for rare object classes.


... establish a consistent improvement over object detectors like DETR and Faster-RCNN, as well as state-of-the-art methods modeling object interrelationships.



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