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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Why class embedding token is added to the Visual Transformer?

In the famous work on the Visual Transformers, the image is split into patches of a certain size (say 16x16), and these patches are treated as tokens in the NLP tasks. In order to perform ...
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What do “spatial” and “temporal” mean in the context of image processing?

I am new to image processing. I am trying to understand CNNs from this blog post. Here's an excerpt from that article that mentions these terms. A ConvNet is able to successfully capture the Spatial ...
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How to change a single object detection network to a multiple object detection network?

I have trained a CNN network to detect a circle and approximate its centre and radius in an image. What I want to do now is detect the centre and radius of all the circles if there are multiple ...
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Bounding box transformation using point cloud

I am working on a project in which I have an RGB Image and the corresponding 2d bounding boxes for the objects in the image. I also have a respective point cloud and therefore, I can extract the depth ...
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11 views

Why the collection of background/negative image dataset is not taught in object detection tutorials and books?

While I was doing an object detection project, I have encountered the problem of getting FALSE POSITIVES and FALSE NEGATIVES. After days of research on StackOverflow, I figured out that I need to ...
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4answers
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How much statistics is involved in AI?

This may be a stupid question but I couldn't really find an answer on the internet. I am a 3rd year math major who is interested in computer science, particularly algorithms and competitive ...
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How to measure(classify) the speed of oncoming traffic via Computer Vision and Neural Networks?

Suppose I have different videos of the same car sometimes moving slow, sometimes moving fast, say, at 50Kmph as slow and 60Kmph as fast. (Assume the background is a green screen and the car doesn't ...
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1answer
19 views

Changing a CNN-LSTM image captioning architecture to use BiLSTMs

Currently I'm dealing with an assignment that made us implement the network mentioned in this paper. The network has an architecture similar to this: As you can see it uses a Unidirectional RNN (in ...
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20 views

How to remember previously detected objects in computer vision?

Let's say I have a drone that has to fly (and scan) over some area (blue on the images - in this case a PV power plant, but it could be anything) in an autonomous way like in the pic below: Let's ...
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18 views

What are the most relevant resources that define the face detection problem formally?

I am new to AI, and I am a bit lost about finding the relevant materials that define the face detection problem formally/mathematically. Can anyone help me formally define face detection, or at least ...
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Arcface implementation for image similarity produces opposite embeddings for positive negative image pairs

So I've built an arcface model with this arcface layer implementation: https://github.com/4uiiurz1/keras-arcface/blob/master/metrics.py I trained for a few epochs and now that I'm comparing the ...
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how to use Laplacian of mesh structure (LBO) for meshes that are registered in deep learning methods based on spectrum (ChebNet for isntance)?

In graph neural network frameworks, there is always a template with a shared structure among all graphs. I have meshes that are registered but obviously, Lalpalcian and their geometry are different. ...
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1answer
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Is intersection of labels acceptable in computer vision?

I have a dataset, where objects are very close to each other. So, the question is: what is the best approach to label them? There are two possible options: mark objects so that they will not ...
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Unet Overfitting for binary segmentation of fake images

I am working on a project where I am trying to detect and localize forgeries in images. I am using the CASIA v2 dataset and using Unet model for the task. I have the binary masks of all the images in ...
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Is it possible to do object detection on an object classification dataset?

I'm new to computer vision, which I find fascinating. I wonder whether it is possible or if there has been any research into going from object recognition data to object detection. In other words, ...
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Can I get some advices on inferencing people from upwards using Yolov5?

I'm trying to inference people from upwards and count them using Yolov5. I know the controversy between yolov5 and yolov4, but for me, Yolov5 is more easier and reliable to use, also the setup. I have ...
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How to obtain part filter anchors in DPM Detector

The DPM detector (https://cs.brown.edu/people/pfelzens/papers/lsvm-pami.pdf) uses latent-svm to train the weights of the root and part filters. During training for positive samples, it alternates ...
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22 views

Which layer to route out of layers of same width and height in Yolo implementation?

In Yolo configuration files (like yolo3.cfg in dark-net), there are many layers with output of same height and width due to ...
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7 views

Should I L-2 Normalise outputs in Siamese Neural Neural Network for distance computation for Triplet Loss or not?

I am building a Siamese Neural Network for Images (CNN) which uses the FaceNet's Triplet Loss as its loss function. I found a good Implementation here where we build a model and the outputs from the ...
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1answer
39 views

Viola-Jones algorithm: Haar-like features, how are the features extracted?

If I have an image like this 1 2 3 4 5 6 7 8 a b c d e f g h ... And I apply a Haar-like feature with a template ...
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2answers
44 views

Should I use U-net to label keys in a keyboard image?

This is a 600*800 image. Which algorithm/model should I use to get an image like the one below, in which each key is detected and labeled by a rectangle? I guess this is some kind of a segmentation ...
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35 views

Is it likely that a sentient AI experience synesthesia?

The reason I ask this question is because we humans tend to compartmentalize our sensory inputs, except in some individuals that experience synesthesia. If an Artificial Intelligence Entity (AIE) can ...
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Mixed precision training - why we're fine with doing point wise operations in FP32

I'm starting to learn more about mixed-precision training, and I'm in particular confused about point-wise operations. In the original article (link), the authors mention, citing: Point-wise ...
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27 views

Resources for Computer Vision Algorithms and Applications

Are there any videos or other books/notes/slides that anyone has come across that follow Computer Vision Algorithms and Applications by Richard Szeliski? We are using this book in class but the ...
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26 views

Can I use the SIFT feature detector on data other than images?

I know how to use SIFT algorithm for images but I never use it for other kinds of data. I have tabular data (x, y, z, time) where x,y,z is the joint position along x, y, z coordinates. Now, can I ...
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How can I improve the robustness of my Fire Detection algorithm in openCV?

I am working on a project to detect fire in CCTV or any other surveillance cameras. Up till now I have completed the following stages; Convert the RGB into HSV Sliced out the Value matrix from HSV ...
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2answers
46 views

What model structure I should use to train on low res and blurry images?

I am looking for advice or suggestion. I have photos like these: photo_1 and photo_2 and many more similar to that. The average shape of these photos is about 160 x 100. What we are doing is we are ...
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1answer
40 views

Should one use an “other” category in image classification?

In image classification, there are sometimes images that do not fit in any category. For example, if I build a CNN in Keras to classify Dogs and Cats, does it help (in terms of training time and ...
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22 views

What is the current approach to topological map building in robotics?

What is the current approach to topological map building in robotics? I suspect topological maps may be the correct approach to robot navigation vs rigid body SLAM, but most of the papers about ...
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Is there any method that combines temporal action proposals with multiple actions' classifiers?

I am trying to classify actions in untrimmed videos. These videos contain a very imbalanced set of actions (where the background class is the majority). I have previously tried frame-wise action ...
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1answer
47 views

Face recognition from single image provided

I am working on a computer vision project, based on face detection to record the time spent by a person in an office. It consists of detecting the face by camera number 1 (input), temporarily storing ...
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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). ...
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Are there any faster and more efficient object tracking algorithms other than DeepSORT and centroid tracker?

Recently, I am trying some algorithm for object tracking, such as DeepSORT and centroid tracker. However, these trackers are slow to run on mobile devices, or even on a single-GPU laptop. Does anyone ...
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What are the metrics to be used for unsupervised monocular depth estimation in computer vision?

I am currently replicating the results of this paper. In this paper they have not mentioned how they are evaluating the results as no ground truth is available for comparison. Same goes for other ...
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1answer
22 views

Is there a methodology for splitting up annotated orthophotos into smaller photos that retain the original bounding boxes?

I'm trying to train an object detection algorithm (i.e. YOLOv4 Scaled, Faster R-CNN) on data taken from large orthophotos. Let's say I have one class, and I label the entire orthophoto with bounding ...
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How to augment 2.5D keypoints?

I am currently working on 3D hand pose estimation. The idea is to first detect the 2.5D pose representation and then obtain 3D pose with the help of camera parameters. For some reason, I was trying to ...
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35 views

CNN leaf segmentation throught classification of edges how to improve

I am trying to design a CNN that can do pixel wise segmentation of edges leaves in dense foliage agriculture images. Such as these: On the basis of this article https://arxiv.org/pdf/1904.03124.pdf, ...
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1answer
75 views

How do you calculate KL divergence on a three-dimensional space for a Variational Autoencoder?

I'm trying to implement a variational auto-encoder (as seen in Section 3.1 here: https://arxiv.org/pdf/2004.06271.pdf). It differs from a traditional VAE because it encodes its input images to three-...
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22 views

Which F1-score is used for the semantic segmentation tasks?

I read some papers about state-of-the-art semantic segmentation models and in all of them, authors use for comparison F1-score metric, but they did not write whether they use the "micro" or &...
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1answer
60 views

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 ...
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34 views

How does the region proposal algorithm in R-CNN work? [duplicate]

I'm trying to understand R-CNN, but I'm a bit lost in the first stage (region proposal). Correct me if I'm wrong, but as far as I understand, there is an algorithm that proposes regions in the image ...
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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 ...
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23 views

Where can I find a progressively trained GAN's pretrained low-resolution models?

StyleGAN is trained progressively, meaning that it starts as a small network trained to produce 4x4 images, then a layer is added which doubles the resolution to 8x8, then 16x16, etc. The final result ...
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44 views

Can I use a CNN for template matching, so that there is robustness, as the background of the target image is not that good?

I have to extract part of a source image, then I have to check if it is similar or almost similar to any of the 10 target images, so that I can do further processing on that one specific target image, ...
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45 views

Object detection approaches without anchors and NMS

The Context From all of the problems I have worked with in computer vision, the most challenging one is the object detection. This is not because the problem itself is complex to understand or bad ...
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How to predict multiple set of coordinates (of bounding boxes) for signboards text localization through neural network?

I am creating a signboard translation application from scratch. I have images of signboards where there are multiple texts and I have the corresponding set of coordinates of bounding boxes for ...
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28 views

How does the embeddings work in vision transformer from paper?

I get the part from the paper where the image is split into P say 16x16 (smaller images) patches and then you have to ...
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2answers
84 views

How to recognize sequence of digits in an image

I am learning to program neural networks and others, and I would like to know how I can get the numbers that are in an image, for example, if I pass an image that has 123 written, get with my model ...
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15 views

Nonrealtime tracking for object detection (with or without deep features)

I've been doing a search for tracking systems based on bounding box for several days (like Sort, DeepSort, Motpy, ...). But neither is nonrealtime. My problem is based on the tracking of multiple ...
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How are the parameters $\alpha_i$ of hard attention trained?

I have a question about Show, Attend and Tell: Neural Image CaptionGeneration with Visual Attention paper by Xu. The basic mechanism of stochastic hard attention is that each pixel of the input image ...

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