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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23 views

How does bipartite matching work in DETR?

I was going through the DETR paper to understand this end-to-end detection transformer used for object detection, and I came across this bipartite matching thing. I searched a little bit, but I was ...
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47 views

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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14 views

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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1answer
27 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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11 views

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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10 views

Role of confidence or classification score in object detection mAP metrics

I know that mAP (mean Average Precision) is the common evaluation metric for the object detection tasks. It uses IoU (Intersection over Union) threshold such as mAP@0.5 to evaluate whether the ...
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1answer
44 views

How to classify two very similar images using Deep Learning?

I am a newbie in Computer Vision. I have a scenario in which I have a stationary camera in a factory. I want to detect whether the technician is working on the machine or not. Images are like the ...
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37 views

How to get bounding box coordinates of all detected objects in yolov5 object detection?

While there is a similar question on stackoverflow, it pertains to yolov4 which, unlike yolov5, uses darknet. Yolov5 is far more intuitive to use than v4 and so a solution to this in v5 is desirable. ...
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Any papers or implementations of Multi label segmentation in pytorch/keras

I am currently working on a project related to Multi label segmentation. I haven't been able to find any substantial papers where objects in images were segmented based on a membership function. For ...
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36 views

Compute IoU for each class in Mask R-cnn

I'm trying to compute the IoU, with the matterport Mask R-cnn implementation, for each class (13 in total) that i have in my dataset. For now i managed to compute the average IoU for all the classes ...
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59 views

In Computer Vision, what is the difference between a transformer and attention?

Having been studying computer vision for a while, I still cannot understand what the difference between a transformer and attention is?
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46 views

Is it possible to use deep learning to generate a 2D image from a few numerical values?

Is it possible to train a DL model that will generate a full resolution 2D image based on few numbers describing this image and what type of model or architecture would that be? What I want to ...
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14 views

Computing the mean attention distance for ViT

Recently I came across the paper that introduces the Vision Transformer (ViT) "AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE". The thing I don't really ...
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10 views

What is language-conditioned visual reasoning?

Can anyone explain what language-conditioned visual reasoning is? I saw this term in this paper and I searched on the internet but I couldn't find a proper explanation.
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52 views

Questions about a research paper on salient region detection and segmentation

I am reading this paper in an attempt to recreate the salient region detection and segmentation model employed. I have the following questions pertaining to section 3 of the paper and I would highly ...
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11 views

Save the Embeddings Model from a Complete Triplet Loss Network

I am working on a Siamese Neural Network with custom Triplet Loss function. As far as I learned from the documentations, we will train a complete network but we want to save only the CNN that is used ...
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13 views

What does the lambda parameter in the paper "Interpretable Explanations of Black Boxes by Meaningful Perturbation" do?

I do not understand the purpose of the $\lambda$ parameter in equation 3 of the paper Interpretable Explanations of Black Boxes by Meaningful Perturbation. $$m^{*}=\underset{m \in[0,1]^{\Lambda}}{\...
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15 views

How can I take continuous video input into my model?

Let's say I have designed an ML model that can take video input of a dog running around and give the breed of the dog as output. However, I do not want to wait for the video to finish before it is ...
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12 views

Comparing results of different image splicing methods on a part of the CASIA 2.0 dataset

So I am working on an image splicing detection algorithm using ResNet-50 model. I am using the CASIA 2.0 dataset which consists of 7491 Authentic images and 5123 Fake images. However out of the fake ...
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45 views

Does randomly adding hand-engineered features increase the CNN's sample efficiency/performance?

It is a known fact that preprocessing images using CV techniques will improve CNN performance (see this answer). But what happens when you feed in the entire image and the filtered image randomly to ...
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17 views

Upscaling a low-res IR image with a high res webcam image

I have a low resolution thermal/IR image (for example 32x32 or 80x64) and a high resolution webcam image. I would like to combine the two to "fake" a high resolution thermal image (I can ...
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19 views

Dissection of a depth map

I am curious about how depth maps work. While searching I came across this website which contains some images and their depth maps. I took this depth map and tried to study it using python pillow. <...
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11 views

How to scale Computer Vision? How to implement Emotion detection from live video feed of N different video simultaneously?

I have a pipeline based on Scaled Yolov4 detection algorithm for faces which extract faces of users and then uses a CNN to ...
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2answers
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Why adversarial images are not the mainstream for captchas?

In order to check, whether the visitor of the page is a human, and not an AI many web pages and applications have a checking procedure, known as CAPTCHA. These tasks are intended to be simple for ...
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3answers
166 views

Why is AI Super Resolution Reconstruction more than just guessing?

I saw a video on Youtube about AI and Super Resolution Image Reconstruction with TecoGAN. I must say I am impressed. Now, I am wondering how reliable this is. I have learned at university that you ...
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10 views

Loss function to Push response value towards extremes

I have a feature map whose values are in the range of [0,1]. I want to push these values either towards extreme 0 or 1 using some loss function. Since I don't have any target value so it had to be in ...
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25 views

How to change number of trained layers in object detection TensorFlow models?

Training custom object detection models with TensorFlow usually means a transfer learning of pre-trained models and, if I understand it correctly, it means only training the few last layers, with ...
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16 views

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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31 views

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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11 views

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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30 views

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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25 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
127 views

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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9 views

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
21 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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19 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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16 views

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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10 views

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
41 views

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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2answers
220 views

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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21 views

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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11 views

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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11 views

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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24 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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11 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
45 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
48 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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