object detection api , coco model

Question

I just started using the tensorflow api and trained few models. Suddenly i realised the name of coco model is different and the accuracy is also the poor like what is the main difference between the faster_rcnn_inception_resnet_v2_atrous_coco Vs faster_rcnn_inception_resnet_v2_atrous_lowproposals_coco VS faster_rcnn_resnet50_coco?? why the terms atrous , low proposals , where in resnet 50 nothing is being used :

https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf1_detection_zoo.md

Answer 1

The naming has to do with the respective submitted variations in the COCO competition and respective papers. They are versions of the Faster RCNN which originally used the VGG-16 for feature extraction.

Not going too deep on this, ResNet Faster RCNN variation, as the name implies, uses the ResNet for Feature Extraction. Then atrous and low proposals are also variations of the model. Atrous:

Atrous Region Proposal Network (ARPN) is proposed to explore object contexts at multiple scales by sliding a set of atrous filters with increasing dilation rates over the last convolutional feature map.

The low proposals, I'm not familiar from where it comes, but from the name, I would guess it just generates less proposals in the Region Proposal Network (RPN) thus being faster at inference time (as you can see in the table of the model zoo).