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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17 views

Is it possible to do object detection on an object classification dataset?

I'm new to computer vision, which I find fascinating. I wonder whether it is possible or if there has been any research into going from object recognition data to object detection. In other words, ...
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7 views

Can I get some advices on inferencing people from upwards using Yolov5?

I'm trying to inference people from upwards and count them using Yolov5. I know the controversy between yolov5 and yolov4, but for me, Yolov5 is more easier and reliable to use, also the setup. I have ...
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11 views

How to obtain part filter anchors in DPM Detector

The DPM detector (https://cs.brown.edu/people/pfelzens/papers/lsvm-pami.pdf) uses latent-svm to train the weights of the root and part filters. During training for positive samples, it alternates ...
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21 views

Which layer to route out of layers of same width and height in Yolo implementation?

In Yolo configuration files (like yolo3.cfg in dark-net), there are many layers with output of same height and width due to ...
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15 views

Pytorch YOLOv4 - Getting low mAP and IoU results [closed]

I am new to computer vision and object detection, and I am using YOLOv4 in Pytorch for the object detection. My end goal is to get my mAP to 60-70% and my IoU to 80-90%. I am trying to detect roadside ...
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7 views

Should I L-2 Normalise outputs in Siamese Neural Neural Network for distance computation for Triplet Loss or not?

I am building a Siamese Neural Network for Images (CNN) which uses the FaceNet's Triplet Loss as its loss function. I found a good Implementation here where we build a model and the outputs from the ...
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1answer
39 views

Viola-Jones algorithm: Haar-like features, how are the features extracted?

If I have an image like this 1 2 3 4 5 6 7 8 a b c d e f g h ... And I apply a Haar-like feature with a template ...
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2answers
35 views

Should I use U-net to label keys in a keyboard image?

This is a 600*800 image. Which algorithm/model should I use to get an image like the one below, in which each key is detected and labeled by a rectangle? I guess this is some kind of a segmentation ...
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35 views

Is it likely that a sentient AI experience synesthesia?

The reason I ask this question is because we humans tend to compartmentalize our sensory inputs, except in some individuals that experience synesthesia. If an Artificial Intelligence Entity (AIE) can ...
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15 views

Mixed precision training - why we're fine with doing point wise operations in FP32

I'm starting to learn more about mixed-precision training, and I'm in particular confused about point-wise operations. In the original article (link), the authors mention, citing: Point-wise ...
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27 views

Resources for Computer Vision Algorithms and Applications

Are there any videos or other books/notes/slides that anyone has come across that follow Computer Vision Algorithms and Applications by Richard Szeliski? We are using this book in class but the ...
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26 views

Can I use the SIFT feature detector on data other than images?

I know how to use SIFT algorithm for images but I never use it for other kinds of data. I have tabular data (x, y, z, time) where x,y,z is the joint position along x, y, z coordinates. Now, can I ...
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7 views

How can I improve the robustness of my Fire Detection algorithm in openCV?

I am working on a project to detect fire in CCTV or any other surveillance cameras. Up till now I have completed the following stages; Convert the RGB into HSV Sliced out the Value matrix from HSV ...
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46 views

What model structure I should use to train on low res and blurry images?

I am looking for advice or suggestion. I have photos like these: photo_1 and photo_2 and many more similar to that. The average shape of these photos is about 160 x 100. What we are doing is we are ...
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1answer
36 views

Should one use an “other” category in image classification?

In image classification, there are sometimes images that do not fit in any category. For example, if I build a CNN in Keras to classify Dogs and Cats, does it help (in terms of training time and ...
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20 views

What is the current approach to topological map building in robotics?

What is the current approach to topological map building in robotics? I suspect topological maps may be the correct approach to robot navigation vs rigid body SLAM, but most of the papers about ...
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Is there any method that combines temporal action proposals with multiple actions' classifiers?

I am trying to classify actions in untrimmed videos. These videos contain a very imbalanced set of actions (where the background class is the majority). I have previously tried frame-wise action ...
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1answer
43 views

Face recognition from single image provided

I am working on a computer vision project, based on face detection to record the time spent by a person in an office. It consists of detecting the face by camera number 1 (input), temporarily storing ...
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40 views

What are the main differences between YOLOv3 and RetinaNet object detection algorithms?

I am looking at a certain project that compares performance on a certain dataset for an object detection problem using YOLOv3 and RetinaNet (or the "SSD_ResNet50_FPN" from TF Model Zoo). ...
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18 views

Are there any faster and more efficient object tracking algorithms other than DeepSORT and centroid tracker?

Recently, I am trying some algorithm for object tracking, such as DeepSORT and centroid tracker. However, these trackers are slow to run on mobile devices, or even on a single-GPU laptop. Does anyone ...
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23 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 ...
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1answer
21 views

Is there a methodology for splitting up annotated orthophotos into smaller photos that retain the original bounding boxes?

I'm trying to train an object detection algorithm (i.e. YOLOv4 Scaled, Faster R-CNN) on data taken from large orthophotos. Let's say I have one class, and I label the entire orthophoto with bounding ...
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17 views

How to augment 2.5D keypoints?

I am currently working on 3D hand pose estimation. The idea is to first detect the 2.5D pose representation and then obtain 3D pose with the help of camera parameters. For some reason, I was trying to ...
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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, ...
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1answer
74 views

How do you calculate KL divergence on a three-dimensional space for a Variational Autoencoder?

I'm trying to implement a variational auto-encoder (as seen in Section 3.1 here: https://arxiv.org/pdf/2004.06271.pdf). It differs from a traditional VAE because it encodes its input images to three-...
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20 views

Which F1-score is used for the semantic segmentation tasks?

I read some papers about state-of-the-art semantic segmentation models and in all of them, authors use for comparison F1-score metric, but they did not write whether they use the "micro" or &...
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1answer
57 views

How to treat (label and process) edge case inputs in machine learning?

In every computer vision project, I struggle with labeling guidelines for border cases. Benchmark datasets don't have this problem, because they are 'cleaned', but in real life unsure cases often ...
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34 views

How does the region proposal algorithm in R-CNN work? [duplicate]

I'm trying to understand R-CNN, but I'm a bit lost in the first stage (region proposal). Correct me if I'm wrong, but as far as I understand, there is an algorithm that proposes regions in the image ...
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21 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 ...
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23 views

Where can I find a progressively trained GAN's pretrained low-resolution models?

StyleGAN is trained progressively, meaning that it starts as a small network trained to produce 4x4 images, then a layer is added which doubles the resolution to 8x8, then 16x16, etc. The final result ...
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43 views

Can I use a CNN for template matching, so that there is robustness, as the background of the target image is not that good?

I have to extract part of a source image, then I have to check if it is similar or almost similar to any of the 10 target images, so that I can do further processing on that one specific target image, ...
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42 views

Object detection approaches without anchors and NMS

The Context From all of the problems I have worked with in computer vision, the most challenging one is the object detection. This is not because the problem itself is complex to understand or bad ...
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10 views

How to predict multiple set of coordinates (of bounding boxes) for signboards text localization through neural network?

I am creating a signboard translation application from scratch. I have images of signboards where there are multiple texts and I have the corresponding set of coordinates of bounding boxes for ...
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21 views

How does the embeddings work in vision transformer from paper?

I get the part from the paper where the image is split into P say 16x16 (smaller images) patches and then you have to ...
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2answers
84 views

How to recognize sequence of digits in an image

I am learning to program neural networks and others, and I would like to know how I can get the numbers that are in an image, for example, if I pass an image that has 123 written, get with my model ...
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14 views

Nonrealtime tracking for object detection (with or without deep features)

I've been doing a search for tracking systems based on bounding box for several days (like Sort, DeepSort, Motpy, ...). But neither is nonrealtime. My problem is based on the tracking of multiple ...
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12 views

How are the parameters $\alpha_i$ of hard attention trained?

I have a question about Show, Attend and Tell: Neural Image CaptionGeneration with Visual Attention paper by Xu. The basic mechanism of stochastic hard attention is that each pixel of the input image ...
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9 views

Aggregating 2D object detections into 3D object detections

I have a data set of 3D images with some bounding box annotations. The images are too large to train something like YOLO 3D (would run out of memory), so I instead created slices of the 3D images with ...
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16 views

Interpreting coordinates of the function from the image using Grid Lines

I have a very different kind of problem at hand. I have a function plotted on the grid lines as shown below Now, I need to get the x and y coordinates for this particular function at regular ...
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20 views

In the DeepView paper, do they use the same FCN for all depth slices AND all views?

I'm trying to replicate a paper from Google on view synthesis/lightfields from 2019: DeepView: View Synthesis with Learned Gradient Descent and this is the PDF. Basically the input to the neural ...
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51 views

What are the pros and cons of 3D CNN and 2D CNN combined with optical flow for action recognition?

For action recognition or similar tasks, one can either use 3D CNN or combine 2D CNN with optical flow. See this paper for details. Can someone tell the pros/cons of each, in terms of accuracy, cost ...
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41 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 ...
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1answer
47 views

Training a classifier on different datasets with different image conditions for different labels causes the model to infer using the background

I have an interesting problem related to training the model on two different datasets for the target feature on images taken on different conditions, which might affect the model's ability to ...
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30 views

Time series analysis using computer vision principles

I'm just starting to explore topics within computer vision and curious if there are any concepts in that area that could be applied to segmenting multivariate time series with the goal of grouping ...
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1answer
41 views

How does general image background removal AI work?

I'm well aware of the inner workings of CNN models for object detection, and although I've not worked on a semantic segmentation problem I can imagine how it works. With these types of models, we need ...
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23 views

How to build a commercial Image-Image search engine using LSH / Near Duplicate or some other algo on more than 20M images

TL;DR: HOW DO I APPLY LSH WITH A DEEP LEARNING MODEL TO BUILD A IMAGE-IMAGE SEARCH ENGINE ON >20M IMAGES? I want to build a system where I am helping my ...
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25 views

Reading Data from a Twilio Stream [closed]

I work for a video tutoring organisation that uses Twilio Video API to carry out the video class. I want to run the object detection and other computer vision models on the input stream. I am stuck at ...
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13 views

Is there a pre-trained network trained on RGB-D (4) channels? [closed]

The most used pre-trained networks for computer vision (e.g. ResNet50) are trained on 3 channels (RGB). At the same time, many cameras used in robotics return RGB-D outputs, that is including depth ...
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1answer
52 views

How to normalize for perceptual loss when training neural net from scratch?

Let's say we are training a new neural network from scratch. I calculate the mean and standard deviation of my dataset (assume I am training a fully convolutional neural net and my dataset is images) ...
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12 views

What are the best metrics for Multi-Object Tracking (MOT) evaluation and why?

I want to compare multiple computer vision Multi-Object Tracking (MOT) methods on my own dataset, so first I want to choose the best metrics for this task. I have carried out some research in ...

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