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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13 views

Where Does Equation (2) in the “Taylor Swift” Paper Come From?

Hi AI Stack Exchange Community, The link to the paper I am referring to is: https://arxiv.org/pdf/2110.14392.pdf I was wondering which theorem of probability is equation (2) (found in page 3 under the ...
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How does a bounding box detection network "know" about absolute position?

I've always found bounding box regression a bit weird. There's no positional encoding like in vision transformers, so how does the network "know" the absolute position when producing ...
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Are there any works that deal with 2D pose estimation in videos?

Since pose estimation is often a task where spatial-temporal context should be helpful in finding subsequent key points, I thought there should be many papers on it. However, I could not find any work ...
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Does adding new keypoints increase accuracy for foot keypoint detection?

I am trying to have better results for foot keypoint detection(or foot pose estimation). In foot keypoints dataset the images labeleld for 6 different keypoints(big,small toes and heel for each foot). ...
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How does the classification head of EfficientDet work?

EfficientDet outputs classes and bounding boxes. My question is about both but specifically I am interested in the class prediction net part. In the paper's diagram it shows 2 conv layers. I don't ...
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30 views

What is the expression for projective transformation?

The following are the two types are projections that are generally used in image processing Affine transformation Projective transformation Affine transformation is a backbone operation in neural ...
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How does Horn–Schunck method for Optical Flow solve the aperture problem?

This is regarding the details stated in Wikipedia. I am reading optical flow in Computer Vision. I understood the Horn–Schunck method as such, but did not get how it is related to the aperture problem,...
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Validity of ImageNet for measurement of the model performance

ImageNet dataset is an established benchmark for the measurement of the performance of CV models. ImageNet involves 1000 categories and the goal of the classification model is to output the correct ...
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Object Center-point detection/tracking without bounding box

The dataset is of microscopic cells. The data format is that it comes with annotations of the center point location of each cell. Usually, the object detection/tracking dataset comes with a bounding ...
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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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What is meant by 2D fourier transform of an image?

I have some questions about this really interesting concept I came across about 2D Fourier transform. Firstly, the Fourier transform of a 1D signal (such as a sound recording) is quite straightforward ...
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Including Object scale/dimension information in features generated by a CNN

I am working on a project where one of the tasks I need to do is to create embeddings for sketches. The sketches in question here are CAD Sketches. Being CAD sketches, the dimension information of the ...
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Predict placement of an object in 3D space

I am trying to find a way to train a model to predict the correct placement of entities like a tree, dog and cat in a natural 3D environment. Any help regarding how I could use textual data to learn ...
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What would be a reasonable option for clustering for unknown number of clusters and a lot of outliers?

I am implementing the CV detection pipeline with the use of SIFT and KNN Matcher. Image keypoints matched to the query keypoints produce the following image: The matched objects have a lot of key ...
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Object detection: when there's only 1 object in each image

Good day. I have a custom dataset for object detection, which has imbalance that each image has only one object annotation. I trained the object detection model(Efficientdet-dx) on TensorFlow object ...
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Encoding Image Priors into CNN

There's a core problem with all of ML which I haven't really seen made explicit: the issue is every model needs to have an assumption on the structure of the data you learn and this assumption needs ...
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What are some applications of virtual try-on other than in the fashion industry?

I've been considering doing research in virtual try-on technology. There are various computer vision techniques that go into this, but I was wondering if there is any potential application of virtual ...
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Which algorithms are used to locate objects in a 3d space?

I can see mobile apps that can locate a 3D object on a surface with a mobile camera and you can turn around that object. What is the name of the algorithm(s) that is used for that purpose? Or, is ...
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37 views

Feature Extraction for printer classification

I need some advice. I am currently trying to do a printer classification with ML/DL. What do I have? 11 colored-images with high resolution from 8 different inkjet-printers (in total 88 images) I have ...
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Is it possible to train an RL agent using images?

I have an image which consists of a start and an end point, the journey has some obstacles which have to be avoided. Is it possible to train an RL agent using such images to find the best path ...
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28 views

How many unique angles of an object do you need in your image training set in order to correctly classify it?

I'm interested in using ResNet-50 to classify images of objects for around 1000 unique classes. I'm wondering if there is any way to estimate how many unique angles I need in my training set to ...
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How can I estimate how many photos I need to train ResNet-50 for image classification?

I am working on a project where I have to classify around 1000 unique objects. I'm trying to plan how much training data I will need to collect. I was planning on using ResNet-50. Is there anyway I ...
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38 views

Can I flip a video to generate more data for action recognition?

There are 8 distinct action classes and around 50+ videos per class. I was wondering if flipping videos from the training set can be a good option to generate additional data. Is it?
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To assess the quality of the reconstructed images, which metric is more reliable: PSNR or LPIPS?

I am training a model for image reconstruction. I used several metrics to assess the quality of the reconstructed images. LPIPS is decreasing, which is good. PSNR goes up and down, but the L1 loss and ...
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Self-Supervised learning model that labels the similar/not similar output?

I want to first reference the following SimCLR framework illustration to explain better what I'm asking. Lets say that after I found out of the image is not similar to the cat, can I actually predict ...
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How do the scale of an embedding affects a downstream task?

I am currently training a neural network in a self-supervised fashion, using Contrastive Loss and I want to use that network then to fine-tune it in a classification task with a small fraction of the ...
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48 views

Do Vision Transformers handle arbitrary sequence lengths the same way as normal Transformers?

Does ViT do handle arbitrary sequence lengths using masking the same way the normal Transformer does? The ViT paper doesn't mention anything about it, so I assume it uses masking like the normal ...
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Non-face "deepfakes" in videos

Instead of changing faces (like James Bond to Putin) what if, given sufficient training data, I wanted to: Remove or add some windows from a brick house? Convert a glass of red wine to a glass of ...
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1answer
56 views

CNN Architectures for local features vs global context

Kaparthy in his blog post said [this] hints at the kinds of architectures we’ll eventually explore. As an example - are very local features enough or do we need global context? I'd like to gain ...
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What is the sensible amount of augmentation?

I am playing with the transforms from Torchvision. There are plenty of different kinds of these like: Resize RandomCrop ...
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Is there any way to remove background of an image fully with the help of post-processor techniques(like edge detector) after deep learning based model

I'm using a deep learning-based model (deep lab v3+ with xception as the backbone) for image segmentation and removing the background. The subject of the image will be a person. And my target is to ...
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Improve generalization of phishing website detection with computer vision

I want to use computer vision to detect phishing websites. There has already been some study on this, which showed this is effective. Most phishing sites try to replicate well-known websites such as ...
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In this paper, how does scaling the filter instead of the image generate saliency maps of the same size and resolution as the input image?

In this paper, in section 3.1, the authors state Scaling the filter instead of the image allows the generation of saliency maps of the same size and resolution as the input image. How is this ...
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Hand Landmark Detector Not Converging

I'm currently trying to train a custom model with TensorFlow to detect 17 landmarks/keypoints on each of 2 hands shown in an image (fingertips, first knuckles, bottom knuckles, wrist, and palm), for ...
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Connection between multi-label classification and multi-class classification

For a dataset with multi-label judgment, e.g., coco dataset but where we only want to predict the most possible label. There're multiple ways: train as multi-label learning and predict as a multi-...
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45 views

What kind of algorithm or approach can I use to find a specific type of object in an image?

What kind of algorithm or approach can I use to find a specific type of object in an image? In particular, I am interested in finding an object like a windmill in an image taken, for example, from ...
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Why the two identical "IoU comparing procedures" are needed in Faster R-CNN(RPN & RCNN)?

As far as I know, there are two same 'IoU comparing procedures' in RPN and RCNN, but why is the same operation held twice? The paragraph right below is what I've comprehended about the Faster R-CNN. ...
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124 views

In this paper, if region $R_{2}$ moves in a sliding window manner, won't the saliency map have a smaller size than the original image?

In the paper Salient Region Detection and Segmentation, I have a question pertaining to section 3 on the convolution-like operation being performed. I had already asked a few questions about the paper ...
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20 views

Monocular depth estimation

I am currently reading the paper towards robust monocular depth estimation and I have 2 doubts about it. First of all the paper stated that there are 2 types of depth annotated, dense and sparse. What ...
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43 views

Why do the object detection networks produce multiple anchor boxes per location?

In various neural network detection pipelines, the detection works as follows: One processes the input image through the pretrained backbone Some additional convolutional layers The detection head, ...
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40 views

What is the fastest multi-human pose estimation model?

I am trying to find an accurate and fast multi-person human pose estimation that I can train on with custom data. I have been searching for a little while and I may not be up-to-date on the newest ...
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67 views

How general is generalization?

I am sorry but I have to explain my question using an example, I do not know how to ask it in proper scientific terms. Let's assume, I have trained a deep learning model on classifying hand gestures, ...
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Is it okay to use publicly available Instagram videos to train an AI?

Since I haven't found any good training data for my university project, I want to use pictures and videos from public Instagram profiles. Am I allowed to do that?
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In anchor based object detection, why don't the anchors share the same weights?

After reading about YOLO V3 and Faster R-CNN, I don't understand why the weights for the regression head aren't the same across all boxes of the same size. Given that the backbone of these systems is ...
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What are the definitions for the content and style of an image without using deep neural network?

In deep learning, an image is said to contain two types of features. One is the content of the image and the other is the style of the image. Deep neural networks are generally used to obtain both ...
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How to ensemble two different computer vision models?

I have prepared two distinct models: Representing contour of the image Representing edges of the image. I would like to create a model which can take advantage of both models in predicting data. May ...
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10 views

Mapping ground truth to downsampled embeddings

I am currently pulling embeddings out of the mid layers of PSPNet. I was wondering if anyone knows of a way to see what pixels in the ground truth map to the pixels in the intermediate layers? e.g. we ...
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is there any proof that metric learning cannot achieve better on image classification task than accepted models (resnet etc)?

Everything is in the title. Metric learning seems to be closer to our way of thinking than the best performing models (supervised learning CNNs-based models like resnet or efficientnet). I was looking ...
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30 views

How to divide a segmented image into classes instances?

Is there a method/algorithm to generate instances of objects from image that was segmented by the use of any image segmentation models? For example, I have an image with one class and it was segmented ...
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How to properly report results for a medical image segmentation task?

Let’s consider a 2-class / binary segmentation problem where c=0 for background (healthy tissues) and c=1 for foreground (...

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