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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.

203 questions with no upvoted or accepted answers
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8
votes
1answer
185 views

Extending FaceNet’s triplet loss to object recognition

FaceNet uses a novel loss metric (triplet loss) to train a model to output embeddings (128-D from the paper), such that any two faces of the same identity will have a small Euclidean distance, and ...
6
votes
1answer
54 views

Video summarization similar to Summe's TextRank

We have the popular TextRank API which given a text, ranks keywords and can apply summarization given a predefined text length. I am wondering if there is a similar tool for video summarization. ...
6
votes
1answer
264 views

Which neural networks are suitable for visual place recognition?

I am doing a project on visual place recognition in changing environments. The CNN used here is mostly AlexNet, and a feature vector is constructed from layer 3. Does anyone know of similar work ...
4
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0answers
2k views

How many training data required for GAN?

I'm beginning to study and implement GAN to generate more dataset. I'll just try to experiment with state-of-the-art GAN models as described in here https://paperswithcode.com/sota/image-generation-on-...
4
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0answers
37 views

How can I improve the performance of a model trained to detect vehicle poses?

I'm looking for some suggestions on how to improve our vehicle image recognition. We have an online marketplace where customers submit photos of their vehicles. The photos need to meet certain ...
4
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0answers
44 views

How do I denoize a microscopic image?

I'm working in a computer vision project, where the goal is to detect some specific parasites, but now that I have the images, I noticed that they have a watermark that specifies the microscope ...
4
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0answers
218 views

YOLO v3 complete architecture

I am attempting to implement YOLO v3 in Tensorflow-Keras from scratch, with the aim of training my own model on a custom dataset. By that, I mean without using pretrained weights. I have gone through ...
3
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0answers
22 views

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 ...
3
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0answers
153 views

Understanding the results of “Visualizing and Understanding Convolutional Networks”

I am trying to understand the results of the paper Visualizing and Understanding Convolutional Networks, in particular the following image: What are these 3x3 blocks and their 9 cells representing? ...
3
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1answer
764 views

How feasible is it to perform pose estimation on a Raspberry Pi 4 using a Pi-Cam?

I want to estimate hand poses and recognize gestures using an open-source library like OpenPose on live video. Considering the fact that such libraries are very computationally intensive. How likely ...
3
votes
1answer
209 views

When training a CNN, what are the hyperparameters to tune first?

I am training a convolutional neural network for object detection. Apart from the learning rate, what are the other hyperparameters that I should tune? And in what order of importance? Besides, I read ...
3
votes
3answers
138 views

If I trained a model to perform semantic segmentation on images with only one object, would it also work on images with multiple objects?

I'm working on semantic segmentation tasks in the medical space using the U-Net. Let's say that I train a U-Net model on medical images with the goal of segmenting out, say, ligaments, from a medical ...
3
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0answers
17 views

Size of image input of neural networks while resizing may not be appropriate

I have the following problem while using convolutional neural networks to detect forgeries: Resizing the image to fit the required input size may not be a good way because the forgery detection ...
3
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0answers
51 views

Ideas on a network that can translate image differences into motor commands?

I'd like to design a network that gets two images (an image under construction, and an ideal image), and has to come up with an action vector for a simple motor command which would augment the image ...
3
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0answers
24 views

Reverse engineering controller sensitivity/aim for several games ie acceleration curves, deadzones, etc

A machine learning project I am working on requires me to interface with an Xbox controller connected to a PC. The implementation must do the following two things: Record the joystick input from the ...
3
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0answers
77 views

Does Retina-net's focal loss accomplish its goal?

Taking out the weighting factor we can define focal loss as $$FL(p) = -(1-p)^\gamma log(p) $$ Where $p$ is the target probability. The idea being that single stage object detectors have a huge ...
3
votes
1answer
515 views

Alternative to sliding window neural network (was: Object detect (or) image classification at specific locations in the frame)

Recent advances in Deeplearning and dedicated hardware has made it possible to detect images with a much better accuracy than ever. Neural networks are the gold standard for computer vision ...
2
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0answers
24 views

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 ...
2
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0answers
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, ...
2
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0answers
45 views

How are nested bounding boxes handled in object detection (and in particular in the case of the SSD)?

The basic approach to non-maximum-suppression makes sense, but I am kind of confused about how you handle nested bounding boxes. Suppose you have two predicted boxes, with one completely enclosing ...
2
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0answers
342 views

Why aren't the BERT layers frozen during fine-tuning tasks?

During transfer learning in computer vision, I've seen that the layers of the base model are frozen if the images aren't too different from the model on which the base model is trained on. However, on ...
2
votes
1answer
48 views

Can we identify only the objects in specific parts of an image with computer vision?

I am studying computer vision for the past 3 months. I have come across the object identification problem, where given an image, CV would identify various parts in the image. If I give an image, and a ...
2
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0answers
30 views

How is the data labelled in order to train a region proposal network?

I don't get how the training of the RPN works. From the forward propagation, I have $W \times H \times k$ outputs from the RPN. How is the training data labeled such that I can use the loss function ...
2
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0answers
87 views

Why can we perform graph convolution using the standard 2d convolution with $1 \times \Gamma$ kernels?

Recently I was reading this paper Skeleton Based Action RecognitionUsing Spatio Temporal Graph Convolution. In this paper, the authors claim (below equation (\ref{9})) that we can perform graph ...
2
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0answers
49 views

What is meant by “arranging the final features of CNN in a grid” and how to do it?

In the paper What You Get Is What You See: A Visual Markup Decompiler, the authors have proposed a method to extract the features from the CNN and then arrange those extracted features in a grid to ...
2
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1answer
69 views

What is a heatmap in the CornerNet paper?

I have been working on understanding how CornerNet works, but I couldn't figure out a few parts about the architecture. First, the authors mention that there are 3 distinct parts to be predicted as a ...
2
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0answers
28 views

Detect object in video and augment another video on top of it

I'm trying to detect an object in a video (with slight camera movement), and then augment another video on top of it. What is the simplest approach to do that? For instance, let's assume I have this ...
2
votes
0answers
28 views

How is visual attention mechanism different from a two branch convolutional neural network?

I am doing some research on the visual attention mechanism in remote sensing domain (where the features learnt from one layer are highlighted using the attention mask derived from another layer). From ...
2
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0answers
32 views

Merge two different CNN models into one

I have 2 different models with each model doing a separate function and have been trained with different weights. Is there any way I can merge these two models to get a single model. If it can be ...
2
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0answers
39 views

Creating Dataset for Image Classification

I want to develop a CNN model to identify 24 hand signs in American Sign Language. I created a custom dataset that contains 3000 images for each hand sign i.e. 72000 images in the entire dataset. For ...
2
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1answer
137 views

Can a fully convolutional network always return an image of the same size as the original?

I'm trying to perform a segmentation task on images of multiple sizes using fully convolutional neural networks. Currently, I'm using EfficientNet as a feature extractor, and adding a deconvolution/...
2
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0answers
57 views

Why are conics important in computer vision?

The book Multiple View Geometry in Computer Vision by Richard Hartley and Andrew Zisserman talks about lines, points and conics. A conic is a curve described by a second-degree equation in the plane, ...
2
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0answers
41 views

Is there an efficient way of determining the layers with the best performance as feature extractors in GoogleNet?

I am using a caffe model of pre-trained GoogleNet trained on ImageNet from here for image retrieval task (place recognition, more specifically). I would like to know the layer with best performance ...
2
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0answers
29 views

Suitable algorithms for classifying terrain condition (asphalt, dirt etc) for motor vehicles

I am required to obtain data through a sensor located on the vehicle reading speed, vibration, roll and tilt, within a sample time, to classify the current road condition using machine learning for a ...
2
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2answers
100 views

Does a fully convolutional network share the same translation invariance properties we get from networks that use max-pooling?

Does a fully convolutional network share the same translation invariance properties we get from networks that use max-pooling? If not, why do they perform as well as networks which use max-pooling?
2
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0answers
25 views

What are the current tools and techniques for image segmentation in order of pragmatism?

To explain what I mean I'll depict the two extremes and something in the middle. 1) Most pragmatic: If you need to just segment a few images for a design project, forget AI. Go into Adobe Photoshop ...
2
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0answers
20 views

Can an image recognition model used for human pose estimation?

I am currently writing my thesis about human pose estimation and wanted to use Google's inception network, modify it for my needs and use transfer learning to detect human key joints. I wanted to ask ...
2
votes
0answers
29 views

SLAM versus “STAM” in vision

In the paper 'Visual SLAM algorithms: a survey from $2010$ to $2016$' by Takafumi Taketomi, Hideaki Uchiyama and Sei Ikeda it is mentioned 'It should be noted that tracking and mapping (TAM) is used ...
2
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0answers
25 views

Ghost camera or video overlays for example in sports

Secondary camera, ghost overlay, video merge... I do not know if what I mean has a more specific name. I wonder if this is a thing. This could be insightful for example in racing sports where ...
2
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0answers
26 views

Confidence Maps and Non-Linearity

I am currently trying to improve a CNN architecture that was proposed for generating depth images. The architecture was originally proposed for autonomous driving and it looks like following : The ...
2
votes
1answer
156 views

What should load_mask() return if an image doesn't have any objects? (Mask RCNN)

I want to use Mask RCNN to do image segmentation. I need to override the load_mask function for the dataset class. I know this function should return mask tensors and class ids of objects in an image. ...
2
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0answers
33 views

How to implement fisherface algorithm and how much time will it take?

I found on the web that fisherface is the best algorithm for face detection. Before investing deeply into it, I just want to know how hard is it to implement it and how much time will it take. I am ...
2
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0answers
26 views

How do I generate structured light for the 3D bin picking system?

I want to know how to generate the structured light which projects different patterns of light on a 3D object which is under scanning.
2
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0answers
12 views

How to use machine learning to create combine of opposite images side by side

Inspired by: Two Worlds Pictures I just want to create a Machine Learning Model that can automatically combine the opposite images into 1 image. I am thinking about 2 possible solutions: Pose ...
2
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0answers
26 views

How can I detect fast and slow motion in videos?

I'm trying to detect if a given video shot is fast or slow motion. Basically, I need to calculate a "video motion" score in a given video sequence, meaning how fast or slow motion the video is. For ...
2
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0answers
19 views

Can Microsoft's cognitive service find similar person in a set of images without using the face service?

I need to create an application that can detect if a person X entered as an input exists in an image set and return as output all the images in which the person X exists. The problem is that the ...
2
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0answers
52 views

Object size identification and maximum number of classes with convolutional neural networks

I am working on a project that involves using a ConvNet to identify screws. I am able to train from scratch a ConvNet based on the first version of the inception network, but shallower (only 3 ...
2
votes
0answers
41 views

Estimate distance between points in perspective image

I am trying to estimate the real world distance (in metres) between two points in a perspective image using an uncalibrated camera. However, the dimensions of an object in the image are known. I ...
2
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0answers
60 views

Transposed convolution as upsampling in DCGAN

I read several papers and articles where it is suggested that transposed convolution with 2 strides is better than upsampling then convolution. However implementing such model with the transposed ...
2
votes
0answers
31 views

Calculating tangent vector of curve s(P,$\alpha$) at given point $\alpha$ = 0

I am reading the paper "Transformation Invariance in Pattern Recognition – Tangent Distance and Tangent Propagation", where the tangent vector is calculated for the given curve $s(P,\alpha)$ at $\...

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