Questions tagged [r-cnn]
For questions related to the family of models known as R-CNN (such as the original R-CNN model, fast R-CNN, faster R-CNN and mask R-CNN).
14
questions
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1answer
18 views
What to do when the ROIs are smaller than $227 \times 227$ in R-CNN?
As English is not my native language, I have some hard time understanding the following sentence:
Regardless of the size or aspect ratio of the candidate region, we warp all pixels in a tight ...
2
votes
1answer
41 views
Is intersection of labels acceptable in computer vision?
I have a dataset, where objects are very close to each other. So, the question is: what is the best approach to label them?
There are two possible options:
mark objects so that they will not ...
0
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0answers
34 views
How does the region proposal algorithm in R-CNN work? [duplicate]
I'm trying to understand R-CNN, but I'm a bit lost in the first stage (region proposal). Correct me if I'm wrong, but as far as I understand, there is an algorithm that proposes regions in the image ...
2
votes
1answer
82 views
Is it possible to pre-train a CNN in a self-supervised way so that it can later be used to solve an instance segmentation task?
I would like to use self-supervised learning (SSL) to learn features from images (the dataset consists of similar images with small differences), then use the resulting trained model to bootstrap an ...
2
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0answers
30 views
How is the data labelled in order to train a region proposal network?
I don't get how the training of the RPN works. From the forward propagation, I have $W \times H \times k$ outputs from the RPN.
How is the training data labeled such that I can use the loss function ...
0
votes
0answers
17 views
How can I decrease the time to compute the mask in the Mask-RCNN for human body detection?
I am using Mask-RCNN to detect human bodies in photos, to get a rough approximation of the ratio of their heights to the length of their chests. I want to decrease the time for making the mask of the ...
1
vote
0answers
29 views
Does the selective search algorithm in object detection learn?
I am trying to get a better grasp of how object detection works. I (almost) completely understand the concept behind RPNs. However, I am a little bit confused with the selective search algorithm part. ...
0
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0answers
15 views
Is RCNN resolution-independent, if keeping feature size constant?
From what I understand, (Faster/Mask-)RCNN is fully convolutional. The backbone is fully convolutional, and the region proposal network (RPN) creates anchors on the feature map with a fixed stride.
...
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0answers
51 views
Since both RoI Align and PrRoI Pooling use bilinear interpolation, why is RoI Align discrete while PrRoI Pooling continuous?
I have two questions.
Since both use bilinear interpolation, why is RoI Align discrete while PrRoI Pooling continuous?
Could anyone explain the intuition behind the derivative of PrPool()?
2
votes
0answers
103 views
Inaccurate masks with Mask-RCNN: Stairs effect and sudden stops
I've been using matterport's Mask R-CNN to train on a custom dataset. However, there seem to be some parameters that i failed to correctly define because on practically all of the images, the bottom ...
2
votes
1answer
89 views
Why are RNNs used in some computer vision problems?
I am learning computer vision. When I was going through implementations of various computer vision projects, some OCR problems used GRU or LSTM, while some did not. I understand that RNNs are used ...
5
votes
1answer
97 views
How does the region proposal method work in Fast R-CNN?
I read so many articles and the Fast R-CNN paper, but I'm still confused about how the region proposal method works in Fast R-CNN.
As you can see in the image below, they say they used a proposal ...
1
vote
1answer
87 views
In Fast R-CNN, how are input RoIs mapped to the respective RoIs in the feature map before RoI pooling?
I've been reading the Fast R-CNN paper.
My understanding is that the input to one forward pass is the whole input image plus a list of RoIs (generated by selective search or another region proposal ...
1
vote
1answer
343 views
In Faster R-CNN, how can I get the predicted bounding box given the neural network's output?
The RPN loss in Faster RCNN paper is
$$
L({p_i}, {t_i}) = \frac{1}{N_{cls}} \sum_{i} L_{cls}(p_i,p_i^*) + \lambda \frac{1}{N_{reg}} \sum_i p_i^* L_{reg}(t_i, t_i^*)
$$
For regression problems, we have ...
