Questions tagged [computer-vision]

For questions related to computer vision, which is an interdisciplinary scientific field (which can e.g. use image processing techniques) that deals with how computers can be made to gain high-level understanding from digital images or videos. For example, image recognition (that is, the identification of the type of objects in an image) is a computer vision problem.

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297 views

What is the state-of-the-art algorithm for neural style transfer?

I've read the paper A Neural Algorithm of Artistic Style by Gatys et. al. and I find the application of neural style transfer very fun. I also read that Exploring the structure of a real-time, ...
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31 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. ...
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66 views

How to make sense of label propagation formula in graph neural networks?

In the label propagation algorithm in section 3.2.3, we know the label of some nodes and we want to predict the label for the rest of the nodes whose labels we don't know. The update formula for this ...
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82 views

Combining clustering and deep learning for computer vision

Is there any recent work on combining clustering approaches (k-means, or gaussian mixture or PGM) with deep learning for computer vision? In particular I'm interested in if anyone has used the first ...
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91 views

Why can we perform graph convolution using the standard 2d convolution with $1 \times \Gamma$ kernels?

Recently I was reading this paper Skeleton Based Action RecognitionUsing Spatio Temporal Graph Convolution. In this paper, the authors claim (below equation (\ref{9})) that we can perform graph ...
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49 views

What is meant by "arranging the final features of CNN in a grid" and how to do it?

In the paper What You Get Is What You See: A Visual Markup Decompiler, the authors have proposed a method to extract the features from the CNN and then arrange those extracted features in a grid to ...
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1answer
59 views

Can I use augmented data in the validation set?

I am trying to predict nursing activity using mobile accelerometer data. My dataset is a CSV file containing x, y, z component of acceleration. Each frame contains 20-second data. The dataset is ...
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1answer
80 views

What is a heatmap in the CornerNet paper?

I have been working on understanding how CornerNet works, but I couldn't figure out a few parts about the architecture. First, the authors mention that there are 3 distinct parts to be predicted as a ...
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45 views

How is depth perception (e.g. in autonomous driving) addressed without using a Lidar or Radar unit?

For practical applications, like autonomous driving, depth perception is needed to make useful decisions. How is this normally addressed without using a LIDAR or RADAR unit (but using a camera)?
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94 views

Is it necessary to label the background when generating the labelled dataset for semantic segmentation?

When I label images for semantic segmentation (using u-net, if that matters), is labeling the background (anything I am not interested in) necessary? Will it improve the network's performance?
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22 views

Best ROC threshold for classifier?

Suppose I have a neural network $N$ that produces the output probabilities $[0.3, 0.8]$. Normally, I would specify a threshold of 0.5 for the argmax of the prediction, let's say, second arg > 0.5 ...
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1answer
93 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 ...
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1answer
77 views

How to prevent image recognition of my dataset with neural networks and make it hard to train them?

Suppose I have a private set of images containing some objects. How do i Make it very hard for the neural networks such as ImageNet to recognize these objects, while allowing humans to do it at the ...
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1answer
106 views

Is it possible to classify resistors using ResNet50?

I want to train ResNet50 model using resistor images like below: I tried it by collecting data from google images and there were quite few. So accuracy was very low (around %10) but I wonder If it is ...
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1answer
60 views

What are some good papers or resources for aspect extraction and opinion modelling from video or audio?

I am quite new to deep learning. I just finished the deep learning specialization by Professor Andrew NG and Deep Learning AI. Now, my professor (instructor) has advised me to look into some classic ...
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30 views

How to determine when the image is steady enough in a video sequence to take photos?

How do I calculate the points in a video sequence where the images are steady enough for a photo. For example, I want to take maybe 20 photos for a facial recognition dataset. Instead of asking the ...
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1answer
57 views

Can imbalance data create overfitting?

I am doing human activity recognition project. I have total of 12 classes. The class distribution look like this: $\color{red}{If \ you \ watch \ carefully, you \ can \ see \ that \ I \ have \ no \ ...
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2answers
2k views

What are the main algorithms used in computer vision?

Nowadays, CV has really achieved great performance in many different areas. However, it is not clear what a CV algorithm is. What are some examples of CV algorithms that are commonly used nowadays and ...
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1answer
126 views

What is a convolutional neural network?

Given that this question has not yet been asked on this site, although similar questions have already been asked in the past (e.g. here or here), what is essentially a convolutional neural network (...
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1answer
1k views

What are bag-of-features in computer vision?

In computer vision, what are bag-of-features (also known as bag-of-visual-words)? How do they work? What can they be used for? How are they related to the bag-of-words model in NLP?
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32 views

Overcome caveats on using Deep Learning for faster inference on limited performance availability

I am working in the field of Machine Vision, where accuracy and performance both play a major factor in deciding the approach towards a problem. Traditional rule based approaches work quite well in ...
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0answers
44 views

What is the reason for different learned features in upper and lower half in AlexNet?

I was reading AlexNet paper and the authors quoted the kernels on one GPU were "largely color agnostic," whereas the kernels on the other GPU were largely "color-specific." The upper GPU takes ...
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1answer
7k views

What is a fully convolution network?

I was surveying some literature related to Fully Convolutional Networks and came across the following phrase, A fully convolutional network is achieved by replacing the parameter-rich fully ...
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30 views

How to calibrate model's prediction given past images?

I want to predict how open is the mouth given a face image. It's a regression problem (0= mouth not open, 1=mouth completely open). And something between 0 and 1 is also allowed. ConvNet works fine ...
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1answer
46 views

Corner detection algorithm gives very high value for slanted edges?

I have tried implementing a basic version of shi-tomasi corner detection algorithm. The algorithm works fine for corners but I came across a strange issue that the algorithm also gives high values for ...
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1answer
161 views

How to choose a suitable threshold value for shi-tomasi corner detection algorithm?

While implementing shi-tomasi corner detection algorithm i got stuck at deciding a suitable threshold for corner detection. In shi-tomasi algorithm all those points that qualify ...
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1answer
40 views

Action recognition using video stream data

Recently, I am working on an action recognition project where my input data is from the video stream. I read some of the concepts like ConvLstm, Convolutional Lstm, etc. I am looking for someone who ...
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142 views

Can we force the initial state of a neural network to produce an "unknown" class?

Has anyone investigated ways to initialize a network so that everything is considered "unknown" at the start? When you consider the ways humans learn, if something doesn't fit a class well enough, it ...
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28 views

Detect object in video and augment another video on top of it

I'm trying to detect an object in a video (with slight camera movement), and then augment another video on top of it. What is the simplest approach to do that? For instance, let's assume I have this ...
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0answers
29 views

How is visual attention mechanism different from a two branch convolutional neural network?

I am doing some research on the visual attention mechanism in remote sensing domain (where the features learnt from one layer are highlighted using the attention mask derived from another layer). From ...
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35 views

Merge two different CNN models into one

I have 2 different models with each model doing a separate function and have been trained with different weights. Is there any way I can merge these two models to get a single model. If it can be ...
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1answer
194 views

How does the math behind heat map filters work?

I am working on an app that generates heat/ thermal map given a picture. i have been able to get what i expected using python opencv builtin function ...
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1answer
108 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 ...
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1answer
1k views

How do you find the homography matrix given 4 points in both images?

I want to understand the process of finding a homography matrix given 4 points in both images. I am able to do that in python OpenCV, but I wonder how it works behind the scenes. Suppose I have ...
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35 views

An Encoder-Decoder based CNN to predict a tensor of points

So I have with me a data of rendered 2D images of a 3D object and along with that, I have the image projection coordinates (X, Y) of all the voxels that are in the ...
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1answer
56 views

How to use 'Canny/Watershed' algorithm's output as an input for Image Classification Model

I have a very silly problem in hand. I have implemented 2 methods which give me the mask to separate the objects from the background. What I get from one method is the object encapsulated in the red ...
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1answer
36 views

Why is this variable in equation 2 of the SQAIR paper a random vector of $n$ ones followed by a zero?

I've been reading the SQAIR paper lately, and the mathematics involved seems a bit complicated. Some background, about the paper: SQAIR stands for Sequential Attend, Infer, Repeat - the paper does ...
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1answer
34 views

Why do we set offset (0.5) in single shot detector?

In the paper SSD: Single Shot MultiBox Detector, under section 2.2 - (4), why do we add an offset of 0.5 to x, y in generating the anchor boxes across feature maps?
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1answer
38 views

If two objects are too close to each other, would an object detector do a poor job of correctly classifying them?

Suppose we have an object detector that is trained to detect $20$ products. If two objects are too close to each other, in general, would an object detector do a poor job of correctly classifying them?...
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0answers
25 views

How come a detection works after global average pooling 2D?

I use an off-the-shelf convolutional neural network, where at the end of the convolutional part, the depth of the last convolutional layer is expanded and then its 2D average is computed (such that ...
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1answer
71 views

What does the Fourier transformed image mean?

I have been trying to figure out what the Fourier transformed image represents. I am aware of Fourier transformation in general, but I can't explain myself the image it forms after transformation. ...
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1answer
51 views

Why are denser layers needed in computer vision neural nets?

Many neural net architectures for computer vision tasks use several convolutional layers and then several fully-connected (or dense) layers. While the reasons for using convolutional layers are clear ...
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2answers
1k views

Could machine learning be used to measure the distance between two objects from a picture or live camera?

Could machine learning be used to measure the distance between two objects from a picture or live camera? An example of this is the measurement between the centre of each eye pupil. This area is ...
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0answers
39 views

Creating Dataset for Image Classification

I want to develop a CNN model to identify 24 hand signs in American Sign Language. I created a custom dataset that contains 3000 images for each hand sign i.e. 72000 images in the entire dataset. For ...
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164 views

Understanding the results of "Visualizing and Understanding Convolutional Networks"

I am trying to understand the results of the paper Visualizing and Understanding Convolutional Networks, in particular the following image: What are these 3x3 blocks and their 9 cells representing? ...
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1answer
216 views

What is "natural image domain"?

I see some papers use the term "natural image domain". I googled that but didn't find any explanation of it. I guess I understand the normal meaning of "natural image", such as the image people take ...
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1answer
823 views

What does "off-the-shelf" mean?

I encountered the phrase/concept off-the-shelf CNN in this paper in which authors used off-the-shelf CNN representation, OverFeat, with simple classifiers to ...
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46 views

What are some real-world products or applications that can be developed using GANs?

GANs have shown good progress across a wide variety of domains ranging from image translation, image generation, text to image synthesis, audio/video generation, image super-resolution and many more. ...
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1answer
288 views

What is a landmark in computer vision?

I guess I understand the concept of face detection, a technique specifies the location of multiple objects in the image, and draws bounding boxes on the target. The question is related to the concept ...
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1answer
69 views

Before GAN, what are the commonly used techniques for image-to-image translation?

As per a post, image-to-image translation is a type of CV problem. I guess I understand the concept of image-to-image translation. I am aware that GANs(generative adversarial networks) are good at ...

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