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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81
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9answers
6k views

How is it possible that deep neural networks are so easily fooled?

The following page/study demonstrates that the deep neural networks are easily fooled by giving high confidence predictions for unrecognisable images, e.g. How this is possible? Can you please ...
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1answer
1k views

Are information processing rules from Gestalt psychology still used in computer vision today?

Decades ago there were and are books in machine vision, which by implementing various information processing rules from gestalt psychology, got impressive results with little code or special hardware ...
12
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3answers
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Measuring Object size using Deep Neural Network

I have a large dataset of vehicles with the ground truth of their lengths (Over 100k samples). Is it possible to train a deep network to measure/estimate vehicle length ? I haven't seen any papers ...
12
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3answers
9k views

Is it difficult to learn the rotated bounding box for a (rotated) object?

I have checked out many methods and papers, like YOLO, SSD, etc., with good results in detecting a rectangular box around an object, However, I could not find any paper that shows a method that learns ...
10
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2answers
1k views

Do deep learning algorithms represent ensemble-based methods?

According to the Wikipedia article on deep learning: Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using a deep ...
9
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3answers
363 views

Detect visual attention area in an image

I'm trying to detect the visual attention area in a given image and crop the image into that area. For instance, given an image of any size and a rectangle of say LxW dimension as an input, I would ...
9
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1answer
3k views

In YOLO, what exactly do the values associated with each anchor box represent?

I'm going through Andrew NG's course, which talks about YOLO, but he doesn't go into the implementation details of anchor boxes. After having looked through the code, each anchor box is represented by ...
8
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1answer
192 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 ...
7
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3answers
326 views

How to use computer vision to find corners of a soccer field based on location coordinates?

I want to use computer vision to allow my robot to detect the corners of a soccer field based on its current position. Matlab has a detectHarrisFeatures feature, but I believe it is only for 2D ...
7
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1answer
119 views

What algorithms are used for segmentation and classification of non solid regions in an image?

In the process of segmentation, pixels are assigned to regions based on features that distinguishes them from the rest of the image. Value Similarity and Spatial Proximity, for example, are two ...
6
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2answers
148 views

Why don't we use auto-encoders instead of GANs?

I have watched Stanford's lectures about artificial intelligence, I currently have one question: why don't we use autoencoders instead of GANs? Basically, what GAN does is it receives a random vector ...
6
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2answers
447 views

Algorithms for scene rotation

My goal is to take an image and return another image that looks as if the scene was viewed from another angle. The difference in angle can be small — let's say as if the hand holding the camera moved ...
6
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3answers
283 views

Has anybody tried unsupervised deep learning from youtube videos?

YouTube has a huge amount of videos, many of which also containing various spoken languages. This would presumably provide something like the data that a "challenged" baby would experience - "...
6
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1answer
149 views

Formal definition of the Object Detection problem

For many problems in computer science, there is a formal, mathematical problem defition. Something like: Given ..., the problem is to ... How can the Object Detection problem (i.e. detecting objects ...
6
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2answers
290 views

Can one use an Artificial Neural Network to determine the size of an object in a photograph?

My question relates to but doesn't duplicate a question that has been asked here. I've Googled a lot for an answer to the question: Can you find the dimensions of an object in a photo if you don't ...
6
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1answer
221 views

Why does nobody use decision trees for visual question answering?

I'm starting a project that will involve computer vision, visual question answering, and explainability. I am currently choosing what type of algorithm to use for my classifier - a neural network or a ...
6
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1answer
1k views

Can reinforcement learning algorithms be applied to computer vision problems?

Can reinforcement learning algorithms be applied to computer vision problems? If yes, what are some examples of these applications?
6
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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
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1answer
265 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 ...
5
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2answers
1k views

What are the main algorithms used in computer vision?

Nowadays, CV has really achieved great performance in many different areas. However, it is not clear what a CV algorithm is. What are some examples of CV algorithms that are commonly used nowadays and ...
5
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2answers
321 views

Is the word “pose” used correctly in the paper “Matrix Capsules with EM Routing”?

In traditional computer vision and computer graphics, the pose matrix is a $4 \times 4$ matrix of the form $$ \begin{bmatrix} r_{11} & r_{12} & r_{12} & t_{1} \\ r_{21} & r_{...
5
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1answer
85 views

How does the region proposal method work in Fast R-CNN?

I read so many articles and the Fast R-CNN paper, but I'm still confused about how the region proposal method works in Fast R-CNN. As you can see in the image below, they say they used a proposal ...
5
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1answer
173 views

Is it feasible to train a Machine Learning Model (with image inputs) in an average personal computer?

There are lots of examples of machine learning systems that can recognize objects and extract other information from images with very high precision. To train the models of such systems is necessary (...
5
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1answer
122 views

Use ConvNet to predict bitmap

I want to build a classifier which takes an aerial image and outputs a bitmap. The bitmap is supposed to be 1 at every pixel where the aerial image has water. For this process I want to use a ConvNet ...
5
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1answer
643 views

Why is image recognition a key function of AI?

Image recognition, in the context of machine vision, is the ability of software to identify objects, places, people, writing and actions in images. Computers can use machine vision technologies in ...
5
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1answer
712 views

Precise localization and characterization of rudimentary shapes with neural networks

I understand that there are flavors of (convolutional) neural networks that are useful for object localization and detection tasks of reasonable difficulty. In all of the examples I have seen so far, ...
5
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2answers
111 views

What are applications of object/human tracking in autonomous cars?

Objects tracking is finding the trajectory of each object in consecutive frames. Human tracking is a subset of object tracking which just considers humans. I've seen many papers that divide tracking ...
4
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1answer
171 views

Why would neural network dream scenes mirror the hallucinations people experience when they're tripping?

In DeepDream wikipedia page it's suggested that a dreamlike images created by a convolutional neural network may be related to how visual cortex works in humans when they're tripping. The imagery ...
4
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2answers
217 views

What is the best approach for writing a program to identify objects in a picture then crop them a specific way?

My works quality control department is responsible for taking pictures of our products at various phases through our QC process and currently the process goes: Take picture of product Crop the ...
4
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1answer
932 views

Applications of CNN for detecting crime from video surveillance cameras

Inspired by this discussion about recognizing human actions, I have found the Fall-Detection project which detects humans falling on the ground from a CCTV camera feed, and which can consider alerting ...
4
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1answer
76 views

Aesthetics analysis with deep learning

I'm trying to score video scenes in terms of aesthetics and cinematography features. Basically, how "interesting" a scene or video frame can be for a viewer. Simpler, how attractive a scene is. My ...
4
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1answer
217 views

Which loss function is the brain optimizing in order to learn advanced visual skills without expert/human supervision?

In computer vision is very common to use supervised tasks, where datasets have to be manually annotated by humans. Some examples are object classification (class labels), detection (bounding boxes) ...
4
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1answer
2k views

What are some tools for labelling images and videos? [closed]

I am looking for AI tools for image and video labeling. It would be great if someone could share its own experience as well suggest tools. I also have some questions Which tools are available? (...
4
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1answer
358 views

What kind of algorithm is used by StackGAN to generate realistic images from text?

What kind of algorithm is used by StackGAN to generate realistic images from text? How does StackGAN work?
4
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1answer
202 views

Which deep learning models are suitable for image-to-image mapping?

I am working on a problem in which I need to train a neural network to map one or more input images to one or more output images (1 channel for image). Below I report some examples of input&output....
4
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1answer
313 views

Name of paper for encoding/representing XY coordinates in deep learning

It this podcast between Oriol Vinyals and Lex Friedman: https://youtu.be/Kedt2or9xlo?t=1769, at 29:29, Oriol Vinyals refers to a paper: If you look at research in computer vision where it makes a ...
4
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1answer
795 views

Training a Yes/No NN for Image Classes

I am fairly a newbie to Neural Networks. I wanted to ask if it is possible to train a NN to identify only one type object? For instance, a table from a large set of images, where the NN should be able ...
4
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1answer
111 views

Video engagement analysis with deep learning

I am trying to rank video scenes/frames based on how appealing they are for a viewer. Basically, how "interesting" or "attractive" a scene inside a video can be for a viewer. My final goal is to ...
4
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1answer
156 views

Object IN/OUT counting using CNN+RNN

I am building a video analytics program for counting moving things in a video. I am detecting bicycles and nothing else. I run object detection using the SSD mobile-net model in all the frames and ...
4
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3answers
984 views

Neural Network for Optical Mark Recognition?

I've created a neural net using the ConvNetSharp library which has 3 fully connected hidden layers. The first having 35 neurons and the other two having 25 neurons each, each layer with a ReLU layer ...
4
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1answer
927 views

Training a CNN from scratch over COCO dataset

I am using Tensorflow Object Detection API for training a CNN from scratch on COCO dataset. I need to use this specific configuration. There is no pre-trained model on COCO with that configuration and ...
4
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2answers
118 views

Kalman filter pre inovation

I am trying to track LIDAR objects using Kalman filter. The problem is that the innovation has the value 0, which makes the Kalman gain be Infinity. Here is a link with the Kalman equations. The ...
4
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1answer
692 views

What are the minimum computing resources needed to train a machine learning algorithm?

For a school project, I would like to investigate a paper on either reinforcement learning or computer vision. I am particularly interested in DQN, RNNs, CNNs or LSTMs. I would eventually like to ...
4
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1answer
762 views

Image comparison algorithm, trying to figure out how similar two “binary” forms are

I'm a student I'm completely new to this technology maybe my approach could be completely wrong, I want to create an algorithm that compares the similarity between two binarized images. I'll explain: ...
4
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1answer
106 views

Can augmented reality be a training system for computer vision?

Is augmented reality a training system for computer vision? As in, Augmented systems use their data to help train computer vision algorithms, or is augmented reality computer vision itself?
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
219 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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1answer
5k views

What is a fully convolution network?

I was surveying some literature related to Fully Convolutional Networks and came across the following phrase, A fully convolutional network is achieved by replacing the parameter-rich fully ...

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