For questions related to the family of models known as YOLO (which stands for "You Only Look Once"), which were proposed by Joseph Redmon et al. There are at least three YOLO models (versions 1, 2, and 3).
Questions tagged [yolo]
80 questions
11
votes
3 answers
Is it difficult to learn the rotated bounding box for a (rotated) object?
I have checked out many methods and papers, like YOLO, SSD, etc., with good results in detecting a rectangular box around an object, However, I could not find any paper that shows a method that learns a rotated bounding box.
Is it difficult to learn…
Ankish Bansal
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9
votes
1 answer
In YOLO, what exactly do the values associated with each anchor box represent?
I'm going through Andrew NG's course, which talks about YOLO, but he doesn't go into the implementation details of anchor boxes.
After having looked through the code, each anchor box is represented by two values, but what exactly are these values…
moondra
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7
votes
2 answers
What's the role of bounding boxes in object detection?
I'm quite new to the field of computer vision and was wondering what are the purposes of having the boundary boxes in object detection.
Obviously, it shows where the detected object is, and using a classifier can only classify one object per image,…
Cody Chung
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6
votes
0 answers
What are the differences between Yolo v1 and CenterNet?
I recently read a new paper (late 2019) about a one-shot object detector called CenterNet. Apart from this, I'm using Yolo (V3) one-shot detector, and what surprised me is the close similarity between Yolo V1 and CenterNet.
First, both frameworks…
Louis Lac
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5
votes
1 answer
In YOLO, when is $\mathbb{1}_{i j}^{\mathrm{obj}} = 1$, and what are the ground-truth labels for $x_i$ and $y_i$?
I'm trying to implement a custom version of the YOLO neural network. Originally, it was described in the paper You Only Look Once: Unified, Real-Time Object Detection (2016). I have some problems understanding the loss function they used.
Basic…
Andrew
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4
votes
1 answer
What is a unified neural network model?
In many articles (for example, in the YOLO paper, this paper or this one), I see the term "unified" being used. I was wondering what the meaning of "unified" in this case is.
Reactionic
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- 3
3
votes
1 answer
YOLO - are the anchor boxes used only in training?
another question in YOLO.
I've red about how YOLO adjusts anchor boxes by offsets to create the final bounding boxes.
What I do not understand, is when YOLO does it.
Is it being done only during the training process, or also during the common use of…
Igor
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3
votes
1 answer
What are the main differences between YOLOv3 and RetinaNet object detection algorithms?
I am looking at a certain project that compares performance on a certain dataset for an object detection problem using YOLOv3 and RetinaNet (or the "SSD_ResNet50_FPN" from TF Model Zoo). Both YOLOv3 and RetinaNet seem to have similar features like…
Ananda
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3
votes
1 answer
How to treat (label and process) edge case inputs in machine learning?
In every computer vision project, I struggle with labeling guidelines for border cases. Benchmark datasets don't have this problem, because they are 'cleaned', but in real life unsure cases often constitute the majority of data.
Is 15% of a cat's…
Huxwell
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3
votes
0 answers
How are Ground truth provided to each Pyramid map in RetinaNet or YOLOv3 Paper? How is the mapping of Feature Pyramids done to Ground Truth
SO the YOLO V3 and RetinaNet both uses the Feature pyramids which look something like this:
(except b and e which have one output)
I'm just confuse how the predictions and training is done?
Do we have to give EACH feature map a different Y label? IF…
Deshwal
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3
votes
0 answers
If random rotations are included in the data augmentation process, how are the new bounding boxes calculated?
When studying bounding box-based detectors, it's not clear to me if data augmentation includes adding random rotations.
If random rotations are added, how is the new bounding box calculated?
FourierFlux
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3
votes
2 answers
Calculation of FPS on object detection task
How to calculate mean speed in FPS for an object detection model like YOLOv3 or YOLOv3-Tiny? Different object detection models are often presented on charts like this:
I am using the DarkNet framework in my project and I want to create similar…
Panicum
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3
votes
1 answer
How can I incrementally train a Yolo model without catastrophic forgetting?
I have successfully trained a Yolo model to recognize k classes. Now I want to train by adding k+1 class to the pre-trained weights (k classes) without forgetting previous k classes. Ideally, I want to keep adding classes and train over the previous…
Troy
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2
votes
3 answers
Would YOLO be able to detect objects in "different" positions?
I have the following question about You Only Look Once (YOLO) algorithm, for object detection.
I have to develop a neural network to recognize web components in web applications - for example, login forms, text boxes, and so on. In this context, I…
giada
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2
votes
2 answers
What YOLO algorithm can I use for images with noise as I will implement it in real time?
I want to detect drivers with or without seatbelts at crossroads. For that, as it is real-time, I am going to use the YOLO algorithm/model. For training data sets (the images) I need to collect, I placed a camera. By recording it and collecting…
ťęjă RAVURI
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