Questions tagged [object-detection]

For questions related to object detection (where objects can be e.g. humans, dogs, houses, etc.), whose meaning or definition can vary depending on the context. OD can refer to the task of locating (i.e. finding the coordinates) an object in an image (so, in this case, it would be a synonym for object localization) or the task of locating the object and classifying it (i.e. object localization + object classification).

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6
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1answer
131 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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1answer
143 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 ...
5
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1answer
135 views

Should I train different models for detecting subsets of objects?

Suppose we have $1000$ products that we want to detect. For each of these products, we have $500$ training images/annotations. Thus we have $500,000$ training images/associated annotations. If we want ...
5
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1answer
87 views

Are there any easy ways to create annotated training images for object detection?

For the purposes of object detection, are there any easy ways to create annotated training images? For example, if we have $10,000$ images and want to draw bounding boxes on 2 objects for each image, ...
4
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0answers
563 views

What are the differences between Yolo v1 and CenterNet?

I recently read a new paper (late 2019) about a one-shot object detector called CenterNet. Apart from this, I'm using Yolo (V3) one-shot detector, and what surprised me is the close similarity between ...
3
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1answer
73 views

Is it possible to train a CNN to predict the dimensions of primitive objects from point clouds?

Is it possible to train a convolutional neural network (CNN) to predict the dimensions of primitive objects such as (spheres, cylinders, cuboids, etc.) from point clouds? The input to the CNN will be ...
3
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1answer
34 views

If two objects are too close to each other, would an object detector do a poor job of correctly classifying them?

Suppose we have an object detector that is trained to detect $20$ products. If two objects are too close to each other, in general, would an object detector do a poor job of correctly classifying them?...
3
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1answer
53 views

Do deeper residual networks perform better or worse?

If you have an $18$ layer residual network versus and a $32$ layer residual network, why would the former do better at object detection than the latter, if you have both models are training using the ...
3
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2answers
60 views

Is the choice of the optimiser relevant when doing object detection?

Suppose that we have 4 types of dogs that we want to detect (Golden Retriever, Black Labrador, Cocker Spaniel, and Pit Bull). The training data consists of png images of a data set of dogs along with ...
3
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2answers
751 views

Calculation of FPS on object detection task

How to calculate mean speed in FPS for an object detection model like YOLOv3 or YOLOv3-Tiny? Different object detection models are often presented on charts like this: I am using the DarkNet ...
3
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1answer
32 views

Is it better to adjust the natural lighting (while recording the video) or to subsequently apply filters on the original video?

For the purpose of object detection, is it better to adjust the natural lighting (while recording the video) or to apply filters (e.g. brightness filters, etc.) on the original video to make it ...
3
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1answer
131 views

How to keep track of the same person detected in different frames of a camera?

At this moment, I am able to use NN to identify an object, such as a human, when given a frame from the camera. Once locate the object, then I can feed the human object image to either NN that's ...
3
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0answers
24 views

Defect Detection System using Deep Learning

What is the general approach to defect detection in deep learning? Would the approach be better if we try to learn the positive images (defects in images) as much as possible or we try to learn the ...
3
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0answers
75 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 ...
2
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3answers
1k views

Small size datasets for object detection, segmentation and localization [closed]

I am looking for a small size dataset on which I can implement object detection, object segmentation and object localization. Can anyone suggest me a dataset less than 5GB? Or do I need to know ...
2
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2answers
138 views

Which neural network is appropriate for measuring object dimensions from stereo images?

I have stereo pairs (left, right) images of concrete cracks. I want to measure the length of the crack from those image pairs. Which neural network is appropriate for measuring object dimensions from ...
2
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1answer
330 views

How can I develop an object detection system that counts the number of objects and determines their position in an image?

I want to create a simple object detection tool. So, basically, an image will be provided to the tool, and, from that image, it has to detect the number of objects. For example, an image of a dining ...
2
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2answers
76 views

What is the best way to detect and recognize traffic signs in a picture?

I'm working on a project for my college to recognize traffic signs in pictures. I searched a lot but can't find the best method to do it. Can someone recommend me a paper, article, or even GitHub link ...
2
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1answer
42 views

Accuracy scores in a Deep Learning project

I'm using three pre-trained deep learning models to detect vehicles and count from an image data set. The vehicles belong to one of these classes ['car', 'truck', 'motorcycle', 'bus']. So, for a ...
2
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1answer
33 views

If an image contains two distinct objects, should I create a copy of this image with distinct labels for each copy?

Suppose we want to detect whether an object is one of the following classes: $\text{Object}_1, \text{Object}_2, \text{Object}_3$ and $\text{Person}$. Should the annotated images only contain bounding ...
2
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1answer
51 views

Why tf object detection api needs so few pictures?

I am wondering why tf object detection api needs so few picture samples for training while regular cnns needs many more? What I read in tutorials is that tf object detection api needs around 100-500 ...
2
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1answer
67 views

How should I detect an object in a camera image?

I would like to create a model, that will tell me if one type of object is in an image or not. So, for example, I have a camera and I would like to see when one object gets into the shot. Object ...
2
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1answer
33 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 ...
2
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1answer
44 views

On which data evaluate an object detection model ? (similar or real life data ?)

I'm training an object detection model (SSD300) to detect and classify body poses in thermal images. Even I have more than 2k different poses, but the background does not change much (I have only 5 ...
2
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1answer
60 views

How does non-max suppression work when one or multiple bounding boxes are predicted for the same object?

My understanding of how non-max suppression works is that it suppresses all overlapping boxes that have a Jaccard overlap smaller than a threshold (e.g. 0.5). The boxes to be considered are on a ...
2
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1answer
52 views

Can a trained object detection model deal with variations of the input?

Suppose an object detection algorithm is good at detecting objects and people when an object and person is close to a camera and upright. If the person walks farther away from the camera and is "...
2
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1answer
58 views

How do I locate a specific object in an image?

Some pictures contain an elephant, others don't. I know which of the pictures contain the elephant, but I don't know where it is or how does it look like. How do I make a neural network which ...
2
votes
1answer
120 views

Understanding a paragraph about object detection with two objects

I was reading this article on detecting rectangles in an image. My doubt is in the part where the model works fine with detecting a single object, but struggles with two rectangles detection. The ...
2
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0answers
27 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
27 views

If random rotations are included in the data augmentation process, how are the new bounding boxes calculated?

When studying bounding box-based detectors, it's not clear to me if data augmentation includes adding random rotations. If random rotations are added, how is the new bounding box calculated?
2
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0answers
21 views

What is the difference between text-based image retrieval and natural language object retrieval?

I'm working on creating a model that locates the object in the scene (2D image or 3D scene) using a natural language query. I came across this paper on natural language object retrieval, which ...
2
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0answers
90 views

Can I resize my images after labeling them?

Is it okay if I label my images with their original size and then resize them, or should I first resize them and then label them? I mean do I need to recalibrate my labels if I resized my images?
2
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0answers
60 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
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0answers
30 views

Can the addition of low-quality images to the training dataset increase the network performance?

I already trained a deep neural network called YOLO (You Only Look Once) with high-quality images (1920 by 1080 pixels) for a detection task. The result for mAP and IOU were 93% and 89% respectively. ...
2
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0answers
39 views

What is the expected value of an IOU in this case?

I have a detection problem. An object with a probability of 0.5 is in a box with coordinates ((0,0), (2, 2)) and with a probability of 0.5 a box with coordinates ((2,0), (4,2)). What is the maximum ...
2
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0answers
19 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
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0answers
40 views

FasterRCNN's RPN network training

I would like to know if my understanding of RPN training is correct, and if never training the RPN on some specific anchor box is bad (i.e if the anchor never sees good nor bad examples). To make my ...
2
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0answers
294 views

How can I train YOLO with the COCO dataset?

I am trying to implement the original YOLO architecture for object detection, but I am using the COCO dataset. However, I am a bit confused about the image sizes of COCO. The original YOLO was trained ...
2
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0answers
14 views

yolo output and how to define labels for backpropogation on it

I want to build the yolo architecture in keras but can't understand the basic idea behind the training of the yolo, like how to define the labels for whether there is no object there what we have to ...
2
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1answer
77 views

Pose estimation using CNNs on Point clouds

In the case of single shot detection of point clouds, that is the point cloud of an object is taken only from one camera view without any registration. Can a Convolutional Network estimate the 6d pose ...
2
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0answers
14 views

How mAP is unfair evaluation metric for Object Detection?

The following figure is from the last page in YOLOv3 paper highlighting how mAP is unfair metric for evaluating Object Detectors: The figure shows two hypothetical Object Detector results which the ...
2
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0answers
49 views

How should I build an AI that quickly detects falling game assets on screen?

I want to build an AI that plays a simple android game. The game is just a one at a time object falling, some times at an angle. The AI needs to recognize the object and to decide whether to swipe ...
2
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0answers
26 views

How to voxelize multiple frames at the time and append them together?

I'm trying to implement this approach for object detection and tracking. In this approach, the first step is voxelize each frame to construct a 3D tensor, the second step is to append multiple voxels ...
2
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0answers
65 views

How to choose our data set wisely?

I have a couple of questions and I was wondering if you could answer them. I have a bunch of images of the cars, side view only. I want to train the model with those images. My objects of interest ...
2
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4answers
209 views

Can bounding boxes further improve the performance of a CNN classifier?

Suppose I have a standard image classification problem (i.e. CNN is shown a single image and predicts a single classification for it). If I were to use bounding boxes to surround the target image (i.e....
2
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2answers
60 views

Recognition of lines in a chalkboard

I'm trying to develop a real-time application that, from the sequence of chalkboard images captured by a webcam, recognizes the lines being draw on it. It must be able of recognize the lines from ...
1
vote
2answers
61 views

How do I label images for deep learning classification?

I have roughly 30,000 images of two categories, which are 'crops' and 'weeds.' An example of what I have can be found below: The goal will use my training images to detect weeds among crops, given an ...
1
vote
2answers
85 views

How to verify classification model trained on classification dataset on a detection dataset for classification purpose?

I am working on a problem that involves two tasks - detection and classification. There is no single dataset for both tasks. I am training two models, separate on detection dataset and another on ...
1
vote
2answers
292 views

What are the reasons behind slow YOLO training?

I'm testing out YOLOv3 using the 'darknet' binary, and custom config. It trains rather slow. My testing out is only with 1 image, 1 class, and using YOLOv3-tiny instead of YOLOv3 full, but the ...