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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When are traditional image processing methods preferable to machine learning and why?

By traditional image processing I understand, e. g. using filters to improve the image, extracting edges and then classifying objects using template matching. My current decision criteria are: large ...
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is there any variation in the results if you resize a image with black lines?

Hello I need to resize a lot of images each of these has its own random size, for example, I have photos with the following size 100x200 102x200 202x201 ... in general, the resolution of each photo of ...
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Does rule-based image processing count as AI?

I'm quite new to the field of AI and I currently find it hard to precisely inclose the broad field of AI. Especially the aspect of image processing isn't quite clear to me. So far I've done rule-based ...
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Current state of the art and datasets for combining NLP and CV?

I was considering a scenario where natural language processing (NLP) and computer vision (CV) are combined, for example in extended reality systems that get as input both natural language and non-...
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What is a "canonical space"?

I am reading the paper on 3D reconstruction, ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction, and I encountered the term "canonical space". What is a "...
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How to compare images for similarity?

I'm working on a system that reads 3 images per second and stores them in a collection. For each image I have all its keypoints and descriptor vectors, using ORB detector. On average there are 250 ...
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Why is my convolutional neural network failing to classify user inputted images after having high accuracy in testing? [closed]

My CNN was trained on the Kaggle A-Z Dataset and consists of: ...
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Is there a model for image pair duplicate detection?

Is there a deep learning model for duplicate image pair detection? Looks like I have to use a Siamese network for this. I have a dataset with image pairs with labelling that they are duplicates or not:...
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Is it possible to add identities into existed face recognition system without re-train the NN?

I have followed some tutorials and I find out all of them could not add new faces. If a new face is added, the system would have to be retrained. This doesn't sound logical because it would waste too ...
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How are 4D cost volumes constructed for DL based stereo matching?

I read a paper on Stereo Matching using Pyramid Cost Volumes (paper link: Semantic Stereo Matching with Pyramid Cost Volumes). At some point, in the proposed architecture, after: Feature extraction ...
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Object Classification: How to decide which detected region is a RoI for classification?

I am working on a project where I am working on the Flickr-47 dataset to do logo detection and classification. My approach is to first finetune a YOLO v5 model with high recall to detect as many "...
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Is it possible to train an AI to bring a picture story in the correct order (correct story flow)?

I want to know if it is possible to train a neural network (or some other kind of an AI) to bring a simple picture story in the correct order, if it is in random order, so that the story has the ...
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For an image (of any object), how to find its location in the other image(s) which contains it, given there are no labels or annotations for any image

Problem Statement: I am given 2 sets of images. All the images in both sets are without annotations and labels. First set : a set of images of the grocery store shelves (captured in the grocery stores)...
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Does redudancy in dataset effect the model's generalization

My current dataset consists of 8000 images along with their corresponding labels which denote the object's coordinates. I am trying to implement a model that predicts the object's bounding box and ...
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Matching a reconstructed 3D Face Model and a 2D Image

I'm working on a project where I should replace the face in the original video with a reconstructed face. I read a lot of articles about keypoints matching and deepfake but there are no pretrained ...
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When generating segmentation mask, is it better for the ground truth mask to be a bit inside the object than outside?

I got asked this question today, and I was wondering. When manually annotating images for ground truth, is it better for the model to get segmentation masks that are a bit inside the object or a bit ...
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Training Variational Autoencoder (VAE) on custom dataset

I am training a VAE on a custom dataset for anomaly detection. The data consists of around 500 images of empty white boxes (at different positions) such as below: Original Image of empty box I am ...
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Performance of augmented dataset with or without original images

I am training on yolo and I had a small dataset. I decided to increase it by augmenting it with rotation, shearing, etc to increase the size and increase accuracy. Now I have seen augmented datasets ...
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CTC Loss incredibly low for wrong output

I am trying to train an OCR model with Vision Transformers. While training the output is a vector with values full of zeros which is obviously padding value. But the CTC loss was small that it was ...
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How do I deal with a dataset of Images with variable sizes (width and height) when doing Image Classification?

I have a dataset in which the images which don't have the same width and height. How do I perform Image Classification with such images? I am trying as much as possible to steer away from image ...
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Training strategy on continuous video stream with CNN-LSTM

I have videos that are each about 30-40 mins long. With the first 5-10 mins (at 60fps, can be down-sampled to 5fps) are one type of activity that would be categorized by label-1 and the rest of the ...
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Does Using the Same Background for Binary Classification Improve Model Accuracy?

I am training a CNN that detects if a there is a pot of boiling water vs if there is a pot of boiling water with pasta inside. My hypothesis is that having the same background for both a positive and ...
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Best approach for object localization of small objects in 3D medical images

I'm working on a project where I try to detect aneurysms (widening of blood vessels) on brain MRI image data (TOF MRAs). I have a dataset of around 290 images. The images are all 128x128x80 px. I have ...
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Arabic words are reversed when I call lstmeval while training in tesseract

I've been trying to train for a new font using Tesseract. It has worked with the default data. But I wanted to train the model for my own generated data which is close to the data that I wanted to use ...
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Head Pose estimation using Car Interiors depth infromation

I am trying to determine head pose of a driver sitting in a car with the depth interiors of the car known to me. Is there any research work which exploits that information in determining the head pose ...
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Image segmentation when given masking information is incomplete

In my problem, there are about 5,000 training images and there are about 50~100 objects of identical type (or class) on average, per image. And for each training images, there is a partial mask ...
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Is it possible to have a heatmap of class activation using a CNN with MaxPooling2D, Flatten, and Dropout in a multiclass image classification?

I noticed that all the tutorials showing how to create a heatmap of class activation are for pre-trained models that use GlobalMaxPooling. Also, since the Flatten layer converts the input to 1D and ...
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Solving logical pattern puzzles with Machine Learning?

I found this kind of problem while reading about some web tests companies use to screen applicants. It is a puzzle where you need to guess what comes inside? Looking at this made me wonder, How would ...
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Why should one focus on spectral operations as a computer vision researcher?

While reading about various types of mathematical operations on tensors, I encountered spectral operations for the first time. The description is as follows (p. 53 of this book) Spectral ops - ...
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What Past Approaches is the "Taylor Swift" Paper Referring To? [closed]

(My previous question regarded which theorem of probability was equation (2) referring to). This paper mentions that temporal forecasting is meant to solve an integral equation as denoted by (2) (...
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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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2 answers
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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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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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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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1 vote
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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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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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2 votes
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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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3 votes
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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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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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2 votes
1 answer
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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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4 votes
1 answer
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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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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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