Questions tagged [non-max-suppression]

For questions about non-max suppression in the context of object detection.

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At which step in faster R-CNN is non-maximum suppression performed?

At which step in faster R-CNN is non-maximum suppression performed? In some book, I have read that it is performed after passing the features through the last fully connected layers, which are located ...
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Avoid unintentional "merging" in cluttered object detection

I have a problem that has bothered me quite some time. With modern methods object detectors can often be accurately trained, even with small to medium sized datasets. However, there is one thing where ...
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Yolo objectness parameter (called p0) vs probability parameters as explained by Joseph Redmon

I have been watching Joseph Redmon (developer of YOLOv3) lecture about YOLO from 45:04 where he explains why he needs both predictions: "objectness" called P0 VS class probabilities called ...
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YOLO - does the Intersection over Union is actually a part of Non Maximum Suppresion

In the Stack Overflow thread Intersection Over Union (IOU) ground truth in YOLO they say that in YOLO actually the IoU (intersection over union) is used twice: during training to compare ground truth ...
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How do I apply non-max suppression for 2-classes problems?

I have basic knowledge about non-max suppression and I know how it works for multiple classes, but what if I want to get a prediction for two classification problems? I give you an example. So I have ...
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How to reject boxes inside each other with Non Max Suppression

I’m working on an object detection cnn, and having some issues with non max suppression. When I have a small box inside a large box, NMS is not rejecting the smaller, incorrect box, because its IOU is ...
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How does Mask R-CNN automatically output a different number of objects on the image?

Recently, I was reading Pytorch's official tutorial about Mask R-CNN. When I run the code on colab, it turned out that it automatically outputs a different number of channels during prediction. If the ...
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How are nested bounding boxes handled in object detection (and in particular in the case of the SSD)?

The basic approach to non-maximum-suppression makes sense, but I am kind of confused about how you handle nested bounding boxes. Suppose you have two predicted boxes, with one completely enclosing ...
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How does non-max suppression work when one or multiple bounding boxes are predicted for the same object?

My understanding of how non-max suppression works is that it suppresses all overlapping boxes that have a Jaccard overlap smaller than a threshold (e.g. 0.5). The boxes to be considered are on a ...
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