Video to Text Description Using Deep Learning and Transformers | COOT
Author(s): Louis Bouchard Originally published on Towards AI. This new model published in the NeurIPS2020 conference uses transformers to generate accurate text descriptions for each sequence of a video, using both the video and a general description of it as inputs. As …
Branches in Artificial Intelligence to Transform Your Business!
Author(s): Jash Rathod Originally published on Towards AI. Artificial Intelligence Exploring Expert Systems, Machine Learning (ML), Robotics, Computer Vision (CV), Natural Language Processing (NLP), and Planning Image from Business Insider On May 8, 2018, Google I/O was held at Shoreline Amphitheatre in …
What is CLIP (Contrastive Language — Image Pre-training) and how it can be used for semantic image search?
Author(s): Vatsal Saglani Originally published on Towards AI. Photo by Maria Teneva on Unsplash Recently, the researchers at OpenAI published a multi-modal architecture that can be used for 30 different tasks once pre-trained on around 400 million image-text pairs. This methodology isn’t …
1. NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis (The first NeRF)
Author(s): YoonwooJeong Originally published on Towards AI. Computer Vision 10 NeRF Papers You Should Follow-up — Part 1 Recommending 10 papers to NeRF researchers. Part 2 will be soon available. Humans generally acquire most information from the eyes. Computer vision has shown …
Why Tensorflow is a great choice for building projects powered by Computer Vision
Author(s): Nour Islam Mokhtari Originally published on Towards AI. Explained by an AI engineer who works on Computer Vision applications Join hundreds of subscribers to my weekly newsletter if you’re interested in learning and staying up-to-date with what’s happening in the field …
Text-to-Drawing Synthesis With Artistic Control | CLIPDraw & StyleCLIPDraw
Author(s): Louis Bouchard Originally published on Towards AI. Take a picture of the style you want to copy, enter the text, and the algorithm will generate a new picture out of it! Example results of input text and style (left), baseline comparisons …
Oriented FAST and Rotated BRIEF (ORB)
Author(s): Garima Nishad Originally published on Towards AI. So first let’s get a general idea about what it does & how it works. Then we’ll see both of these algorithms separately i.e. FAST and BRIEF. Fast and brief, are a feature detection …
APTOS 2019 Blindness Detection — Playing around with ResNeXts and Progressive NASNet
Author(s): Luka Chkhetiani Originally published on Towards AI. APTOS 2019 Blindness Detection U+007C Towards AI A while ago Kaggle announced challenge: APTOS 2019 Blindness Detection — Detect diabetic retinopathy to stop blindness before it’s too late. The idea of competition is to …
StyleGAN Generated Face Classification with ResNexts
Author(s): Luka Chkhetiani Originally published on Towards AI. Using ResNexts with StyleGAN U+007C Towards AI https://generated.photos A week or two back a team released a dataset of 100K images of generated faces, based on StyleGAN [Karras et al. and NVIDIA] (see paper). …
How R-CNN Works on Object Detection?
Author(s): Edward Ma Originally published on Towards AI. Introduction to Region with Convolutional Neural Networks (R-CNNs) Photo by Edward Ma on Unsplash Region with Convolutional Neural Network (R-CNN) is proposed by Girshick et al. in 2013. It changed the object detection field …
Reinventing Greeting Cards Through Augmented Reality
Author(s): Limarc Ambalina Originally published on Towards AI. An Interview with iGreet’s Founder With the holiday season quickly approaching, greeting card companies around the world are rolling up their sleeves and preparing for their busiest time of the year. However, the Bulgaria-based …
Number Plate Detection — DETECTRON v2
Author(s): Luka Chkhetiani Originally published on Towards AI. Most (well, at least some) of the ‘Smart Cameras’ don’t use number plate detection & recognition systems, but they pay attention to specific hidden codes on the number plates, and by sticking some transparent …
Attention! Beginners, Theory: Challenging terms and Methods for Facial Features Recognition
Author(s): Surya Govind Originally published on Towards AI. Theory Explained ( Computer Vision ): Pattern recognition ( Facial Recognition ) with Challenges and possible methods Image by newsroom.cisco.com from Laurence Cruz Energy-saving tip folk: Better start with OpenCV-C++/ Python, https://docs.opencv.org/2.4/modules/contrib/doc/facerec/facerec_tutorial.html is a …
![[2019-CVPR] D2-Net: Matching Problem among Images Under Extreme Appearance Changes](https://i2.wp.com/miro.medium.com/v2/resize:fit:1800/1*YTRPXUakFV6cA92PwHYjbw.png?w=1440&resize=1440,687&ssl=1 "[2019-CVPR] D2-Net: Matching Problem among Images Under Extreme Appearance Changes")
[2019-CVPR] D2-Net: Matching Problem among Images Under Extreme Appearance Changes
Author(s): YoonwooJeong Originally published on Towards AI. Using computer vision on a dome. This article is based on the paper ‘D2-Net: A Trainable CNN for Joint Description and Detection of Local Features,’ which is published in 2019-CVPR. For further read, refer https://arxiv.org/pdf/1905.03561.pdf …
Custom Object Detection using EfficientDet- The Simplest way
Author(s): Akula Hemanth Kumar Originally published on Towards AI. Object Detection In this article, I am going to show you how to create your custom object detector using Monk’s EfficientDet. I am assuming that you already know pretty basics of deep learning …
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