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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Getting an error importing SWin transformer using tensorflow in colab
I am trying to load swin transformer from tfhub as follows but on loading the model I get an error.
def load_model(): model_url = "https://tfhub.dev/google/swin_transformer/...
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Are there deepfake detection technologies available outside of the major companies?
I've been reading a lot about deepfakes lately and it's got me wondering about how we can detect them. I know big tech companies like Google and Facebook are working on this, but what about the rest ...
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Is residual mapping always beneficial?
While reading the residual learning paper [1], I found a problem to be quite unanswered. Suppose I am stacking a deep neural network to map an input to a output. Lets say a function H(x) does the ...
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What is the current state of the art in video transformers (mainly for tasks like classification) and what are the Top 5 papers from the last 2 years?
Is there a general consensus in the community regarding
the most effective video transformer architecture
which modalities to use, how to represent them, and the best methods for fusing them
the ...
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What is "Explicit Propagation" Image Inpainting - LatentPaint Paper - Generative AI
I am trying to implement "Explicit Propagation" method for Image Inpainting introduced in LatentPaint Research paper.
This paper proposes the introduction of a module between VAE and ...
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Seeking Advice on Triangulation Error Using GPS-Enabled Drone Images in Rerun Visualization Software
I am currently working on a project where I am triangulating a point using multiple images captured by a GPS-enabled drone. The images have been reconstructed using software such as Reality Capture ...
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Application thats compatible with android that allows you to access the wifi signals around you and constructs its own
Can we develop a application thats compatible with android that allows you to access the wifi signals around you and constructs its own?
By continuously encryption data by the wifi signal by ...
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Seeking Advice on Optimizing a Computer Vision Ensemble for 500 Cameras
I hope you are all doing well. I'm reaching out to this community to seek your advice and insights regarding a project I'm currently working on.
Thank you in advance for any help or suggestions you ...
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Is there a better way to do this type of optimization?
I have an image classification task that uses an object detection model as its basis. For each image, I get a vector of confidences (one value for each class), and I take the class with the highest ...
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Deep Learning training strategy: Avoid shuffling individual training images, instead shuffle batches?
I am training a YOLO (You only look once) object detector for an application within an industrial environment. Since a fixed setup of cameras is used, the backgrounds of the images are camera-...
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Understanding MOTChallenge dataset format
I was looking into MOT17 datasets. And I have some stupid questions regarding dataset:
Q1. Why there is no ground truth files in test datasets? For example ...
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Why is the CLIP model sometimes referred to by the name of its image encoder only (e.g., ViT-B/32)?
I've noticed that in some discussions, the CLIP model is referred to by the name of its image encoder only, such as "ViT-B/32." However, CLIP consists of both an image encoder and a text ...
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Understanding matching of a CNN Layer's Output With the Receptive Field of Input Layer
I was trying to implement the following paper: https://arxiv.org/abs/1610.01563 and I came across something that seemed ambiguous to me. On page 4, second paragraph, it says
After processing the ...
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Geometry adaptive kernel estimation for crowd counting based on bounding box dimensions
I'm generating a ground truth density map set for an object counting task involving different object classes. The objects are labeled with bounding boxes (i.e [class, x, y, w, h]), which vary in size ...
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Spatial vs spatiotemporal methods for object counting in low frame-rate videos
I'm currently working on an object counting/density estimation task using low frame rate video (~2 fps) in a traffic setting. I've explored a lot of literature on both spatial methods (i.e. using only ...
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Why can't we use only keys to calculate self-attention?
I was reading about the self-attention mechanism and the paper suggests to have 3 things to be computed: Key, Query and Value. As far as I understood the reason for having Value is to allow ...
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Fuse Feature Vector in image classification?
Currently, i'm processing a image classification problem about facial emotional classification. I am using 2 extract methods: HOG and Facial Landmark. My idea is using HOG to find the gradient ...
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Can a transformer detect same object with different sizes?
Suppose a vision transformer has trained to detect this cat picture
Next we show it another picture of a zoomed-in cat (taken from the same image) and asked it to identify the picture
The linearized ...
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Improve Performance of License Plate Recognition using EasyOCR
I wish to extract the license-plate text from images using EasyOCR.
I am obtaining license-plate images from a 2MP camera's stream placed atop traffic light poles. ...
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Is there an algorithm capable of telling knots and links apart?
I'd like to create some algorithm that can tell apart knots from links.
A knot is made up of one line, a link with multiple. As input, we expect images as above.
Is there an algorithm capable of ...
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Can the output of non-max suppression have more bounding boxes than the number of objects the picture actually has?
I am not really understanding the non-max supression (NMS) algorithm. Let's say my model produces 20 bounding boxes (bbs) for my picture which have 7 cats (7 objects with the same class). Can it be ...
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Can 3D convolutions appropriately capture a frozen embedding space?
My project is a strange combination of NLP and Computer Vision.
I have datapoints of 3D tensor where each element is a token in an NLP vocabulary. The vocabulary is around 1000 unique "words"...
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Realtime cuboid vs cylinder classification of a 2D mask / object from a 3D scene?
Most realtime SOTA segmentation/detection model can reliably segment an object from a 2D input, and I can get the contours/polylines describing its edges in realtime. By realtime, I'll consider ...
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Why does UNet often output noisy pattern in blank/homogeneous region?
I am recently implementing DDPM model from scratch, and I discovered that UNet often tends to give noisy output in blank region. Here is an example with FashionMNIST, my DDPM seems to generate OK ...
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Good models for building/tree detection
I need to estimate the speed of a car by analysing a dashcam video that provides a view of the street in front. I had the idea of tracking objects that I know are stationary (buildings/trees) and ...
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Trained model on cifar10 performs poorly on real images
So I'm trying to train a model using the CIFAR10 dataset.
The problem is that while the performance of the model on validation and test sets are good (about 95-96%), the model fails to predict images ...
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Why different noise in GAN generate different images?
I understand that noise $z$ serves as the input to the generator. Noise $z$ is essentially a vector of random numbers, typically from Gaussian distribution with chosen size of like $100$. However, I ...
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Image segmentation with noisy labels
I have a dataset which consists of satellite images and their labels which are indicated by let say class 1 and 2.
I want to perform image segmentation to detect pixels related to class 1 and 2. The ...
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Glass Degradation Video Prediction
We are working on the subject above, where a sequence of $n$ glass frames forms an example with an associate target that is a video of the glass future state.
We would like to know if there exists an ...
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Enhancing Soil Moisture Predictions Using Multimodal Data Integration in Agriculture
I am exploring an interdisciplinary research area involving multimodal data, focusing on agriculture. My study incorporates both visual and tabular data: crop and soil images from three distinct ...
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KD-loss between intermediate feature maps of different channels
Assume a teacher model and a student model. Teacher is bigger than student in terms of depth and/or width, however, comes from the same "family".
In addition to the loss that involves the ...
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Marking object on a map from the image
I have been researching if there are any existing machine learning models that would help mark objects (for example: cars) on the map having only image, camera location, and camera orientation.
For ...
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adversarial training on convnext shows a very strange curve
i am currently working on a research project where I have to train some models for adversarial robustness. I have implemented the algorithm used by a research paper called adversarial training for ...
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SOTA model (PAtt-lite) implementation with Pytorch [closed]
I'm trying to implement a model guided by the paper of PAtt-lite (weights are on https://github.com/jlrex/patt-lite but no implementation provided yet). Using FER2013+ and RAF-DB. The main classes I'...
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Classifying Images that Look Like Noise
I'm about to build a system that is supposed to evaluate images (900 x 150) like the following and classify it in to one of five categories:
image that looks like noise
In case you're wondering, they'...
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How to estimate the weight of quarry material in a pile
A quarry wants to know the weight of materials they extract from the quarry. I was thinking they could use some computer vision to estimate the weight based on a 3D generated model of the quarry ...
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Using computer vision to comprehend Piping and Instrumentation Diagrams
I'm wondering how to approach this problem. I want to create an excel document (or just a dictionary) where each instrument (circle objects FV 1031, for example) is associated with a line number (for ...
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Can T-Net be substituted by data augmentation in the PointNet architecture?
I am looking at the PointNet architecture at I was wondering why T-Net was preferred over data augmentation.
Correct me if I am wrong, but I think of T-Net as trying to find a transformation that will ...
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How to calibrate IMU for large scale deployments possibly using deep neural network
We were testing our visual SLAM algorithm on robots. We were getting poor performance. Then we calculated wite noise and random walk parameters (using kalibr) for the IMU and used it in our algorithm ...
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How does the Yolo loss match bounding boxes to the ground truth?
I've been going over the YOLO paper again and I was wondering something about the loss.
Yolo divides an image into grids and then for each grid can have multiple bounding boxes to detect multiple ...
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What are efficient methods for classifying tremor intensity, given challenges with 3D CNN and memory issues with a pretrained VideoMAE model?
I have a training dataset of 80 videos (without augmentation). They are 15 seconds video recorded at 30fps and 240*480 dimensions. What options do I have to train a classification model? The problem ...
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Handle overlapping objects in instance segmentation annotation
As I struggle to find any literature online about this, I wanted to create a discussion that other would be able to learn from.
My question is inspired from a Yolo GitHub issue.
In this example we ...
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In neural style transfer, why do we focus on a single style image?
In all the descriptions of neural style transfer that I've seen so far, there is a single style image and a single content image, and the task is to produce a new image with the style of one image and ...
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Is global pooling necessary in image classification models? [closed]
In many image classification models, the global pooling operation is performed before the classification layer (i.e. fully connected layer) to reduce model complexity. Is the global pooling layer a ...
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does it make sense to consider the base/backbone network one of the multiscale feature map blocks in SSD?
I'm trying to understand Single Shot Multibox Detection following a book adopted at 500 universities from 70 countries
The complete single shot multibox detection model consists of five blocks. The ...
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High Fluctuations in Validation Curve
Below I attach an image of accuracy curves. I got a lot of suggestions regarding some improvement in below curves. Following are my experiments in order to make the curve stable-->
I used lr = 4....
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ViT fails to detect a white pixel in a black image
I wanted to report you to some experiments in the context of Deep Learning for Computer Vision, in particular for visual reasoning.
The main question I am trying to answer is the difference between ...
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Do GANs have constant running time?
After the model is trained, you just need to input random noise and the generator will output an image, does this mean GANs have constant running time ? I'm asking about both naïve GAN and variants of ...
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Question about the Conditioning Augmentation technique?
In the paper StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks, the goal is to convert text descriptions into images. The text encoder encodes the ...
user78202