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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19 views

Object Detection as a means of Anomaly Detection

Is it possible to train an Object Detector (e.g. SSD), to detect when something is not in the image. Imagine an assembly line that transports some objects. Each object needs to have 5 screws. If the ...
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34 views

Face detection and replacement in photos

I have 2 photos, and my goal is to detect the face in one and place it on the face of the person in the other photo- basically face detection and replacement. It's not deep fakes. It's more of a ...
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29 views

Why do we need to provide false labels to the discriminator on purpose to train GANs?

This is the tutorial that I used to learn about GANs. In this tutorial, it taught us to intentionally provide false labels to "fool" the discriminator, but does it make the discriminator ...
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101 views

How to compute dominant colors in an image?

I was trying Google Cloud's Vision API, and how the dominant colors part shows. I uploaded a sample image, and here is the results for the dominant colors. I realized it doesn't simply count pixel ...
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33 views

How does one measure image similarity using Radial Basis Kernel?

Here is the formula of a radial basis kernel $$ k\left(x_{i}, x_{j}\right)=\exp \left(-\frac{d\left(x_{i}, x_{j}\right)^{2}}{2 l^{2}}\right), $$ where $x'$ and $x$ are feature vectors. I have two very ...
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29 views

What is a "center loss"?

I have seen that a center loss is beneficial in computer vision, especially in face recognition. I have tried to understand this concept from the following material A Discriminative Feature Learning ...
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24 views

Generating data from a High-Res. RGB image for a CNN

Say I want to build a detection model that detects the existence of X or NO X. The only piece of information I have, though, is a high res. RGB image, say 100k (width) x ~1000 pixels (height). Let's ...
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Find object's location in an area using computer vision

I'm trying to see how to detect the location of a soccer ball in the field using the live camera. What are some ways to achieve this? 1- Assuming we have a fixed camera with a wide shot. How to find ...
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1answer
161 views

Why do we resize images before using them for object detection?

In object detection, we can resize images by keeping the ratio the same as the original image, which is often known as "letterbox" resize. My questions are Why do we need to resize images? ...
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42 views

Distinguishing between handwritten compound fraction and subtraction

I am working in a project named "Handwritten Math Evaluation". So what basically happens in this is that there are 11 classes of (0 - 9) and (+, -) each containing 50 clean handwritten ...
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50 views

Deep Learning based image restoration using multiple frames

Suppose we have a sequence of still images each of which has been contaminated by some particles(ex, dust/sand/smoke) making the images very poor in certain areas. What architecture would be best to ...
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1answer
42 views

Are there any known models/techniques to determine whether a person in a store is a customer or a store representative?

Are there any known models/techniques to determine whether a person in a store is a customer or a store representative? For example, customer representatives can wear uniforms and then one possible ...
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68 views

Are Markov Random Fields and Conditional Random Fields still used in computer vision?

Back before deep learning, there were a lot of different attempts at computer vision. Some involved Conditional Random Fields and Markov Random Fields, which were both computationally difficult and ...
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54 views

Computer vision - Can you put more weight on a specific part of the object?

Let's say I'm looking for any item that has a certain shape (outline) in a photo. but I can further classify it only according to particular features, that most of them are expected to be shown only ...
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2answers
462 views

What is the need for so many filters in a CNN?

Consider the following coding line related to CNNS Conv2D(64, (3,3), strides=(2, 2), padding='same') It is a convolution layer with filter size $3 \times 3$ and ...
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1answer
63 views

How can I train a CNN to detect when a person is smoking outside of shop given images from a video camera?

My friend is working at a pizza shop. He takes cigarette breaks in an area that is covered by the public webcam of our town. I now want to train a convolutional neural network to be able to detect ...
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1answer
25 views

Is training a CNN object detector on an image containing multiple targets that are not all annotated will teach it to miss targets?

I want to train a convolutional neural network for object detection (say YOLO) to detect faces. Consider this image: In this training image, I have many people, but only 2 of them are annotated. Is ...
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471 views

Why aren't the BERT layers frozen during fine-tuning tasks?

During transfer learning in computer vision, I've seen that the layers of the base model are frozen if the images aren't too different from the model on which the base model is trained on. However, on ...
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11 views

What is a wavefront algorithm?

I am designing and researching algorithms which I call of a wavefront nature. It is image analsyis agorithms when every pixel may change many times during the processing. I have heard this name before,...
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1answer
154 views

Formal definition of the Object Detection problem

For many problems in computer science, there is a formal, mathematical problem defition. Something like: Given ..., the problem is to ... How can the Object Detection problem (i.e. detecting objects ...
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18 views

How do you make a regression model from a binary labeled dataset?

Suppose I have a dataset with hand images. Hand completely opened is labeled as 0 and hand completely closed (fist) are labeled as 1. I also have a bunch of unlabeled images of hands which, if ...
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10 views

Train 3D object detection model for custom object

I am trying to train a model that can detect a 3D object and give me a 3D bounding box around it. For this, I have a RGBD camera and a 2D LiDAR. Most of the research is done for cars/cyclists/...
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35 views

How to use SPP-net and what are its drawbacks?

I read about the spatial pyramid pooling concept, it's really cool! Now, my doubt is how to find the number of layers to use, and in each layer what should be the grid sizes when using spp. But, I ...
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35 views

Would it be possible to use AI to measure pupil dilation diameters and fluctuation, on video films on a regular webcam?

I've been researching the topic of Cognitive Load Measurement through pupil dilation measurement. All solutions to pupil dilation measurement require some kind of special hardware setup. I was ...
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1answer
76 views

Can we identify only the objects in specific parts of an image with computer vision?

I am studying computer vision for the past 3 months. I have come across the object identification problem, where given an image, CV would identify various parts in the image. If I give an image, and a ...
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41 views

How to normalise image input to backpropogation algorithm?

I am implementing a simple backpropagation neural network for classifying images. One set of images are cars another set of images are buildings (houses). So far I have used Sobel Edge detector after ...
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1answer
38 views

Is there any network/paper used to analyse music scores?

As I am curious on music theory I would like to know that If is there any such network that analyse like labeling chords, or doing a roman numeral analysis. Like an example below: Source It does not ...
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159 views

Why don't we use auto-encoders instead of GANs?

I have watched Stanford's lectures about artificial intelligence, I currently have one question: why don't we use autoencoders instead of GANs? Basically, what GAN does is it receives a random vector ...
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29 views

How do non-local neural networks relate to attention and self-attention?

I've been reading non-local neural networks as explained in the original paper. My understanding is that they solve the restrained reception of local filters. I see how they are different from ...
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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 ...
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19 views

How can traditional edge detection algorithms be implemented on a GPU?

How can edge detection algorithms, which are not based on deep learning, such as the canny edge detector, be implemented on a GPU? For example, how are non-edge pixels removed from an image once it ...
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1answer
62 views

Why isn't medical imaging improving faster with AI?

Researcher here. I just read this piece about medical imaging ai with object recognition and it left me wondering why there are still 100,000+ deaths a year in the US due to misdiagnosis - anyone out ...
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42 views

How to train the images of various sizes?

I am practicing with an image dataset which is having different dimensions. If I simply crop and pad them to 1024X1024(the original images having smallest width is around 300 and largest is around ...
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22 views

Object detection using CNN model architectures

I've used LabelImg to create labels for my images using YOLO. After that, I would like to input the images and labels into a CNN model, like a VGG or ResNet. I've searched a lot and have not found ...
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24 views

How to calculate the attention loss in the paper "Tell Me Where to Look: Guided Attention Inference Network"?

I have been reading the research paper Tell Me Where to Look: Guided Attention Inference Network. In this paper, they calculate the attention loss, but I didn't understand how to calculate it. Do we ...
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2answers
41 views

How to take the optimal batch_size for training a model?

I have an image dataset, which is composed of 113695 images for training and 28424 images for validation. Now, when I use ImageDataGenerator and ...
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1answer
93 views

What do we mean by 'principal angle between subspaces'?

I came across the term 'principal angle between subspaces' as a tool for comparing objects in images. All material that I found on the internet seems to deal with this idea in a highly mathematical ...
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2answers
47 views

Technology for predicting body measurements of a person, with a full body photo of them

I am working on making an app that would require the ratio of the height and the largest width of a person, in order to group the individual into a certain body fat percentage category. In short, I ...
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1answer
69 views

Is there any real-time computer vision system that can learn to detect new objects of new classes?

Suppose you have a ground plane and can use a stereo vision system to detect things that are possibly separate objects. Suppose also your robot or agent can attempt to pick up and move these objects ...
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1answer
40 views

How does YOLO handle non-class objects?

I have been reading more about computer vision and I'm bothered by YOLO and similar deep learning architectures. The thing I am confused about is how non-class image sections are dealt with. In ...
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15 views

Is there a problem for "Sound Source Identification in Video Footage"?

I've been considering starting a project for some time on sound source identification. To be more specific, my goal is to be able to identify the "sources" for sound in videos. Moving parts ...
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1answer
271 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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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. ...
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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
56 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
77 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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