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.

Filter by
Sorted by
Tagged with
0
votes
0answers
10 views

Which metrics of COCO API are suitable for object detection

These days I train a person detector and I use COCO API to evaluate my model. It uses Recall and Precision to evaluate a detection task. It's output is something like this: ...
2
votes
1answer
30 views

What are sim2sim, sim2real and real2real?

Recently, I always hear about the terms sim2sim, sim2real and real2real. Will anyone explain the meaning/motivation of these terms (in DL/RL research community)? What are the challenges in this ...
0
votes
0answers
15 views

How to recognize two different objects with the similar shape, but different size

I am using Mask-RCNN neural network. I retrained my network to detect and mask wheels of die-cast toy cars. I am using images, which present the side of the car (left or right). Sometimes the cars ...
0
votes
0answers
9 views

What is best dataset for person reidentification?

There are many datasets for person reidentification. I want to train a robust person re-identification neural network. Therefore I want to ask about best person re-identification dataset.
0
votes
0answers
9 views

what is the best dataset (or combination of datasets) for training a person detector?

I want to train a person detector for MOTChallenge dataset, but I want to avoid using the dataset as training set for my detector. Therefore, I want to use another dataset or combination of several ...
0
votes
0answers
10 views

How much data is needed to train a deep learning model to detect instance masks?

I am trying to get an idea of how much data is needed to train a deep convolutional neural network to detect instance masks from images. I am interested in both papers that have been written on the ...
1
vote
1answer
30 views

How well can ConvNET distinguish an object from its class?

ConvNET can easily predict class of an object in an image. My question is, can ConvNET distinguish Pisa Tower from other buildings or Hagia Sophia from other mosquoes easily? If it can, how many ...
2
votes
0answers
19 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 ...
3
votes
1answer
70 views

Is there any computer vision technology that can detect any type of object?

Is there any computer vision technology that can detect any type of object? For example, there is a camera fixed, looking in one direction always looking at a similar background. If there is an object,...
1
vote
1answer
15 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. ...
1
vote
0answers
24 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 ...
1
vote
1answer
60 views

Ideas for a computer vision project

I'm working towards getting into a Computer Vision-based tech team in college. To get in, I have to impress my college seniors with an independent project. The team works on autonomous driving, so any ...
2
votes
1answer
48 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 ...
2
votes
2answers
37 views

Dealing with empty frames in MRI images

I started working on the application of deep learning in medical imaging recently. While dealing with MRI images in the BraTS dataset, I observe that first and last few frames are always completely ...
1
vote
0answers
23 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.
4
votes
0answers
22 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 such ...
2
votes
1answer
34 views

How to generate the original image from feature set?

We all know that using CNN, or even simpler functions, like CLD or EHD, we can generate a set of features out of images. Is there any ways or approaches that given a set of features, we can somehow ...
3
votes
4answers
186 views

What could an oscillating training loss curve represent?

I tried to create a simple model that receives an $80 \times 130$ pixel image. I only had 35 images and 10 test images. I trained this model for a binary classification task. The architecture of the ...
1
vote
0answers
7 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
votes
2answers
52 views

Why do we get a three-dimensional output after a convolutional layer?

In a convolutional neural network, when we apply the convolution on a $5 \times 5$ image with $3 \times 3$ kernel, with stride $1$, we should get only one $4 \times 4$ as output. In most of the CNN ...
2
votes
1answer
55 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
votes
0answers
19 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. ...
1
vote
1answer
37 views

What is the difference between 2d vs 3d convolutions?

I was trying to understand the definition of 2d convolutions vs 3d convolutions. I saw the "simplest definition" according to Pytorch and it seems the following: 2d convolutions map $(N,C_{in},H,W) \...
2
votes
0answers
18 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
votes
2answers
49 views

How should we pad an image to be fed in a CNN?

As everyone experienced in deep learning might know, in an image classification problem we normally add borders to images then resize it to the input size of a CNN network. The reason of doing this is ...
0
votes
2answers
41 views

Untrained CNNs as feature extractors?

I've heard somewhere that due to their nature of capturing spatial relations, even untrained CNNs can be used as feature extractors? Is this true? Does anyone have any sources regarding this I can ...
2
votes
0answers
15 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 ...
1
vote
0answers
16 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
votes
0answers
38 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 ...
1
vote
0answers
10 views

Extracting Descriptors and feature points for 3d mesh

I'm programming my work with python, and I have a mesh and I want to extract 3d descriptors and feature points from it( trying to work on multi-scale strategy) , to visualize them later on the mesh, ...
2
votes
1answer
28 views

What does the words “coarse” & “fine” means in the context of computer vision and semantic segmentation?

I was reading the well know paper Fully Convolutional Networks for Semantic Segmentation and throughout the whole paper they talk use the term fine and coarse. I was wondering what the meant. The ...
1
vote
1answer
37 views

How do I identify the number and type of objects in the same picture?

I need to identify the number and type of all objects in a picture, so there can be multiple objects of the same type. For example, I have a picture with $10$ animals, and I want my program to tell ...
0
votes
0answers
17 views

How can I convert the annotations produced by LabelImg to labels for Yolov2?

I was recommended to use LabelImg to create annotation labels for YOLOv2. However, the annotations look something like this: 4 0.517500 0.597500 0.915000 0.735000 (classes and 4 coordinates x,y,w,h)...
2
votes
1answer
18 views

Is this technique image processing or computer vision?

If I use my mobile camera on a signboard or announcement board on a road or in a street (like the one attached in photo) where the message is written in Russian and my mobile shows me that message in ...
3
votes
1answer
61 views

What is the difference between image processing and computer vision?

What is the difference between image processing and computer vision? They are apparently both used in artificial intelligence.
0
votes
0answers
10 views

When should I stop the object detection model training while mAP are not stable?

I am re-training the SSD MobileNet with 900 images from the Berkeley Deep Drive dataset, and eval towards 100 images from that dataset. The problem is that after ...
2
votes
1answer
45 views

What is “dense” in DensePose?

I've recently come across an amazing work for human pose estimation: DensePose: Dense Human Pose Estimation In The Wild by Facebook. In this work, they have tackled the task of dense human pose ...
0
votes
0answers
139 views

Applying a 1D convolution for 4D input

i'm trying to implement this paper and I'm stuck for quite some time now. Here is the issue: I have a 3D tensor and has (180,200,20) as dimension and I'm trying ...
0
votes
1answer
59 views

YOLO Architecture - kmeans clustering

In YOLO, why use k-means clustering to determine bounding-box priors ? Why if we use standard k-means with Euclidean distance, larger boxes generate more error than smaller boxes? Why using IOU (...
2
votes
1answer
40 views

Are there any better visual models for transfer rather than ImageNet?

Similar to the recent pushes in Pretrained Language Models (BERT, GPT2, XLNet) I was wondering if such a thrust exists in Computer Vision? From my understanding, it seems the community has converged ...
1
vote
0answers
11 views

Understanding average precision (AP) in measuring object detector performance

I am trying to understand the average precision (AP) metrics in evaluating the performance of deep-learning based object detection models. Suppose we have the following ground true (four objects ...
0
votes
0answers
61 views

YOLO architecture

1) How (Is it possible) to combine Fast-RCNN (2-stage) and YOLO (1-stage)? 2) Why with the addition of anchor boxes we changed the resolution to 416 x 416? Why using anchor boxes we get a small ...
2
votes
1answer
34 views

How does ARKit's Facial Tracking work?

iPhone X allows you to look at the TrueDepth camera and reports 52 facial blendshapes like how much your eye is opened, how much your jaw is opened, etc. If I want to do something similar with other ...
0
votes
1answer
114 views

Autoencoder for MobileNetV2

I have way more unlabeled data than labeled data. Therefore I would like to train an Autoencoder using MobileNetV2 as the encoder. Then I will use the pretrained model for the classification of the ...
0
votes
1answer
54 views

What is wrong with this CNN network, why are there hot pixels?

I'm building a CNN decoder, which mirrors (in reverse) the VGG network structure from Conv-4-1 layer. The net seems to be working fine, however, the output looks broken. Please note that the colour ...
2
votes
1answer
33 views

Which API can I use for tracking the position of animal in one or more images?

I'd like to build an application for tracking the position of a given animal (e.g. a cat) in a series of images. Is there any off-the-shelf API I could use? Azure has some Vision APIs, but it seems ...
1
vote
0answers
34 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 ...
0
votes
0answers
6 views

Super resolution of an object in a video using adjacent frames

Video frames super-resolution with deep learning? I've been searching for the whole day and could find no papers\projects tackling that problem. For example: suppose I have a series of N frames of ...
2
votes
0answers
20 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 ...
0
votes
0answers
15 views

Bigger receptive field

I have a network which has a input size of (28x28x1) and since I'm using (3x3 convolution) so the receptive field is (3x3). Before going further I will show the code snippet ...