Questions tagged [computer-vision]

Questions related to image representation, segmentation, visual object categorization and image processing algorithms in general.

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11 views

How to compute feature-space distance?

some CV research papers use nearest neighbors techniques to compare images, such as PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION Next five rows: Nearest neighbors ...
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Non-linearity (ReLU, Batch Norm) before final sigmoid convolution in image segmentation

When building an image segmentation model, standard building blocks consist of Conv -> RELU -> Batch Norm -> DropBlock. I understand the importance of having a non linear activation, and the role that ...
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Optical flow equation understanding [closed]

Optical flow: I have been experimenting to extract flow data from a set of video files. The video files have all kinds of motions ( local, global and translation and rotation and slow and fast). Based ...
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Extreme Image Noise Removal

I've been trying to solve a noise removal (from images) problem using deep learning and I've tried a lot of the newer architectures for noise removal including FFDNet, NLRN and MWCNN. The problem is, ...
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1answer
22 views

How does Stochastic Gradient Descent with momentum distinguish between local minima and global minima?

I have several questions regarding this. How does SGD momentum know to converge at global minina and skip over local minima? I read that "SGD momentum goes past the minima (due to its velocity build ...
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What happens when the filter size is same as that of image size in a CNN?

In Convolutional Neural Networks (CNNs), theoretically speaking, if the filter dimensions are same as that of the image (training example) dimensions, will CNNs boil down to normal Fully Connected ...
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12 views

Intersection vs Chi-Square for comparing histograms

I've seen lots of examples where chi-square works better. But is there any example of for ex. 3 non-similar histograms where Intersection results in the similarity of histograms but Chi-square results ...
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6 views

Techniques for estimating homography

Is there any good comparison of methods (SIFT+RANSAC, SURF, MSER, ConvNets...) for estimating homographies / finding correspondencies? Or, if you have experience in this topic, what would be the best (...
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Why Resnets Converge Faster? [closed]

According to the Research Paper: Deep Residual learning for Image Recognition, the 18-layer plain/residual nets are comparably accurate , but the 18-layer ResNet converges faster. What is the reason ...
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Annotation of dataset for object detection

I am annotating a dataset for object detection of UI elements (buttons, text, edit text, etc..) in images of phone screens and I am wondering what is a better approach. If I want to detect buttons (...
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How to visualize 3d joints of a SMPL model based on pose params

I am trying to use demo.py in https://github.com/nkolot/GraphCMR. I am interested in obtaining joints from the inferred SMPL image and visualize it similar to ...
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Pre-training a network on significant landmarks

Let's say there is a dataset consisting of photos of cars from various brands, and we're trying to train a ConvNet to identify the brand from a photo, just like these ones: One approach I was ...
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Can Graph Neural Networks be better than Convolutional Neural Networks for computer vision tasks? [closed]

Recently, a strong trend in deep learning is the adoption of Graph Neural Networks for computer vision tasks (https://github.com/thunlp/GNNPapers#computer-vision). But the main question is could this ...
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2answers
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How can a given conv neural net layer handle filters of different size?

traditional method is to use multiple filters of same dimensions but with different weights and stack the output (basically concatenate them) that is then to be fed into the next conv layer. If I ...
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1answer
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Are there any Non Neural Network models to do face detection in constrained domains?

In some constrained domains(eg: car driver), the camera is stationary which means the background will not change much. And we can sure when the car is running, there must be a driver. In this kind of ...
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How to develop a Deep learning model for only two Imges …?

I am trying to build Deep learning model for only two Images. I have a two images of doors , one image is some what good and another is some what bad, I want to identify the one is good and another ...
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Is object detection the right approach for this problem

I'm trying to build a model which, given a picture of someone's face, is able to identify all the following features, as well as others. The model would output, for each picture, a list of all the ...
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Computer vision with smaller data set

I hope this is the right forum to ask. I had a client approach me with a demand for a vision system for their assembly line. The problem they are facing is that the operator sometimes forgets to put ...
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1answer
27 views

How to use additional non-visual data for image classification?

I've got a Resnet network that classifies images into n classes and is working fine. I want to boost its performance buy using additional information I have regarding the images. This info comes in ...
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1answer
19 views

Looseness of the definition of domain adaption

I am a bit intrigued about “domain shift” concept. Specifically, in part 5 of the paper “Coupled Generative Adversarial Networks”, it reads We studied the problem of adapting a digit classifier ...
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Reading a pressure gauge with a CNN

Using standard Computer Vision pipelines to read pressure gauges is well established, and not overly accurate or generalizable: For various reasons, I would like to use a CNN to do this. Since the ...
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1answer
22 views

Analysing the impact of each CNN layers

I want to analyse the impact of each layer of CNN. I have trained the CNN model with a dataset. After that, weights of first convolutional layer are fixed and remaining layers are initialise to zero ...
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30 views

Retraining of object detection CNN

I am working on an object detection system that should detect UI elements (such as button, checkbox, radio button, etc..) in the photo of a touch screen of printer (not screenshots, but literally a ...
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17 views

Semantic Segmentation Multi-Class Single Channel Output Math

For semantic segmentation problems, I understand that it's a pixel-wise classification problem. At the last layer of the neural network, I would basically have a 1x1x1 convolution layer with a softmax ...
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1answer
28 views

Performance of MaskRCNN/YOLO as a function of object size in pixels

I am trying to find references on how the resolution of an object affects the ability of object detection systems such as MaskRCNN and YOLO to correctly identify the object. For example, if the ...
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1answer
26 views

Incorrect predictions on extracted images from text [closed]

I trained a model in PyTorch on the EMNIST data set - and got about 85% accuracy on the test set. Now, I have an image of handwritten text from which I have extracted individual letters, but I'm ...
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video normalization using skvideo

I'm building a model that would take as input a video of 25 frames and would (ideally) output the next 25 frames. My question is when we use images we usually normalize by dividing the X by 255. ...
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13 views

Image classifier from text files

I have a data set of thousands of images of hundreds of pixels in gray scale ranging from -1 to 1. The labels represent 0 to 9. The issue is that the data set is in .txt format. How can one make an ...
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1answer
88 views

Same value of min and max in min-max normalisation

By the definition of min-max normalisation, the value is divided by max - min, what if the max and ...
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48 views

Karush-Kuhn-Tucker Conditions in a Biometrics Research Paper

For one of my course works I'm supposed to find a scientific paper from my field of research that involves an optimisation problem solution based on the Karush-Kuhn-Tucker conditions. My research ...
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1answer
71 views

What would be the ideal dataset to train a model to detect advertisements in an image?

I am thinking of the requirements for training a model that would be able to detect if there is any kind of ad in an image. I know that this sound too broad not just for a question on CV but for ...
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3answers
730 views

Which image format is better for machine learning .png .jpg or other?

I'm trying to train a neural network with images. Since I'm extracting images from a video feed I can convert them either to .png or .jpg. Which format is preferred for machine learning and deep ...
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0answers
19 views

Reconstruction using low-light images

Let's say we have a regular photo and three low-light photos illuminated in different colors. Each pixel is a three-component vector $q=(R,G,B)$. Then $q_k^{A}$ is the $k$-th pixel of the regular ...
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1answer
91 views

Understanding the weighted cross-entropy method of u-net

I am trying to implement the weight-cross entropy mentioned in unet paper to counter the class-imbalances. I am not really able to understand how they are exactly implementing the weight-cross entropy....
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1answer
54 views

Object detection : Multimodal or single input ? for Depth + Thermal images

I need to detect persons in a scene. I have a 16 bits depth image of that scene (640, 480) I have a 16 bits thermal image (80, 60) of the same scene (slighly different point of view) I resize these ...
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0answers
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Understanding the concept behind Microsoft Computer Vision- Analyze an Image. Also extract metadata of image from different search engines

My task is to upload an image and get as much information as I can get about the image or in different words its metadata (not exif) like - what is it, caption, price, what does it do, application, ...
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1answer
29 views

Semantic segmentation mask

What does the mask look like when doing semantic segmentation. I have 3 classes (background, liver, tumour). Currently the input to my segmentation model looks like this (32, 128, 128, 3) where 32 =...
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1answer
34 views

Object classification

I'm currently working on a "Where's Waldo" project as part of my coursework, where I have to find 3 different characters in any given image - Waldo, Wenda, and Wizard. I'm trying to convert this ...
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0answers
21 views

Shape classification by color - computer vision

I have task of classification of polygons. These shapes may differ only by color, or be transformed by linear transformation (scaled, rotated). I am using ORB for separating different polygons, but it ...
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1answer
35 views

Object detection with just one image? [duplicate]

Deep neural networks require lots of examples to learn tasks like image classification, and object recognition. On the other hand, we humans can learn and identify object just by looking at it once. ...
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1answer
54 views

batch size of stochastic gradient descent [duplicate]

I understand that stochastic gradient descent has a batch size of 1, but while reading inception v2 paper, I found this text in training methodology "We have trained our networks with stochastic ...
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1answer
42 views

Is there a difference between training with multiple objects in a single image and multiple objects in a different images?

I'm trying to generate data for my object detection network (which will be used for TensorFlow: ResNet). What I'm currently curious about is this: if I have the same total amount of data (each data ...
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0answers
33 views

Is there a model or algorithm to improve digital drawings?

given a bad drawing, the algorithm should deform the edges of the bad drawing and fill them with color so that it looks more like a learned character. the entry would be a very poorly made drawing of ...
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0answers
25 views

Impact of increasing number of classes on object detection rate/speed

I am trying to build a Darknet (C++) model to detect custom objects. Initially, in the testing phase for 50 objects with tiny yolo, I am getting 35 FPS speed. If I increase the number of objects to ...
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1answer
52 views

Is it possible to train a model to detect a shape? [closed]

We have multiple object detection APIs that can help us to find the bounding box coordinates. But is it possible to go a little further and find/separate the shape of the object (say cat/dog/human) ...
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21 views

What do I do when my deep learning model in CNN does not learn? [duplicate]

I'm training on a skewed image dataset of 5000 images with class weights. The training loss decreases well and swift, but the validation-set loss fixates after around 6 epochs. I have tried using my ...
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1answer
95 views

Object distortion after ROI Align in Mask R-CNN

In Mask R-CNN, if there are 2 proposed ROIs which cover 2 objects that looks like below: #1 A square object #2 A rectangular object So my question is: After ROI Align, is the #2 feature map ...
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1answer
33 views

Mode-collapse problem in GAN: How to grasp the full entropy of the distribution we want to model in GAN

In pix2pix GAN paper( https://arxiv.org/abs/1611.07004), authors found that the noise vector and the dropout are not efficient in grasping the full entropy of the data distribution we want to model. ...
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8 views

Model for simultaneous person detection and pose estimation

Does someone know a model that performs person detection (eg using a bounding box like YOLO or Mask-RCNN) and simultaneously pose estimation (like CPM or Personlab) in one forward pass. The models I ...
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1answer
147 views

Training an Object Detection Model Using with Artificial Data from Video Games

I had an interesting idea of using artificial data gathered from screen shots of a high-resolution video game as a cheap substitute for labeled real data, which can be quite expensive or difficult to ...

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