Transformers are a very powerful Deep Learning model that has been able to become a standard in many Natural Language Processing tasks and is poised to revolutionize the field of Computer Vision as well.It all began in 2017 when Google Brain published the paper destined to change everything, Attention Is All You Need [4]. Researchers apply this new architecture to … [Read more...] about On Transformers, TimeSformers, And Attention
Computer Vision
New Ways To Leverage AI Image Synthesis For Marketing & Advertising Content
This research summary is part of our AI for Marketing series which covers the latest AI & machine learning approaches to 5 aspects of marketing automation:AttributionOptimizationPersonalizationAnalyticsContent Generation: ImagesContent Generation: VideosContent Generation: TextAfter Generative Adversarial Networks (GANs) were introduced by Ian Goodfellow in 2014, a … [Read more...] about New Ways To Leverage AI Image Synthesis For Marketing & Advertising Content
Novel AI Methods For Video Generation for Marketing & Advertising
This research summary is part of our AI for Marketing series which covers the latest AI & machine learning approaches to 5 aspects of marketing automation:AttributionOptimizationPersonalizationAnalyticsContent Generation: ImagesContent Generation: VideosContent Generation: TextAI algorithms can significantly increase the efficiency of the original content generation … [Read more...] about Novel AI Methods For Video Generation for Marketing & Advertising
Step-By-Step Implementation of GANs on Custom Image Data in PyTorch: Part 2
In Part 1 on GANs, we started to build intuition regarding what GANs are, why we need them, and how the entire point behind training GANs is to create a generator model that knows how to convert a random noise vector into a (beautiful) almost real image. Since we have already discussed the pseudocode in great depth in Part 1, be sure to check that out as … [Read more...] about Step-By-Step Implementation of GANs on Custom Image Data in PyTorch: Part 2
How I Would Explain GANs From Scratch to a 5-Year Old: Part 1
Note: Quite frankly, there are already a zillion articles out there explaining the intuition behind GANs. While I will briefly touch upon it, the rest of the article will be an absolute deep dive into the GAN architecture and mainly coding — but with a very very detailed explanation of the pseudocode (open-sourced as an example by PyTorch on Github).Why do I need … [Read more...] about How I Would Explain GANs From Scratch to a 5-Year Old: Part 1
Why Is Object Detection So Messy?
Those working with Neural Networks know how complicated Object Detection techniques can be. It is no wonder there is no straight forward resource for training them. You are always required to convert your data to a COCO-like JSON or some other unwanted format. It is never a plug and play experience. Moreover, no diagram thoroughly explains Faster R-CNN or YOLO as there is for … [Read more...] about Why Is Object Detection So Messy?
Transformers in Computer Vision
Transformer architecture has achieved state-of-the-art results in many NLP (Natural Language Processing) tasks. One of the main breakthroughs with the Transformer model could be the powerful GPT-3 released in the middle of the year, which has been awarded Best Paper at NeurIPS2020.In Computer Vision, CNNs have become the dominant models for vision tasks … [Read more...] about Transformers in Computer Vision
Deep-Learning Based Object Detection in Crowded Scenes
Object detection in crowded scenes is challenging. When objects gather, they tend to overlap largely with each other, leading to occlusions. Occlusion caused by objects of the same class is called intra-class occlusion, also referred to as crowd occlusion. Object detectors need to determine the locations of different objects in the crowd and accurately delineate their … [Read more...] about Deep-Learning Based Object Detection in Crowded Scenes
NeurIPS 2020 Papers: Takeaways for a Deep Learning Engineer – Computer Vision
As mentioned in part 1– the most important thing:) – I went through all the titles of NeurIPS 2020 papers (more than 1900!) and read abstracts of 175 papers, and extracted DL engineer relevant insights from the following papers.This is part 2. See part 1 here.If this in-depth educational content is useful for you, you can subscribe to our AI research mailing list to be … [Read more...] about NeurIPS 2020 Papers: Takeaways for a Deep Learning Engineer – Computer Vision
NeurIPS 2020: Key Research Papers in Computer Vision
Our team reviewed the papers accepted to NeurIPS 2020 and shortlisted the most interesting ones across different research areas. Here are the topics we cover:Natural Language Processing & Conversational AIComputer VisionReinforcement Learning & MoreTackling COVID-19 with AI & Machine LearningIf you’re interested in the remarkable keynote presentations, … [Read more...] about NeurIPS 2020: Key Research Papers in Computer Vision