Summary: Autonomous vehicles (AUVs) and many other systems that need to accurately perceive the world around them will be much better off when image classification moves from 2D to 3D. Here we examine the two leading approaches to 3D classification, Point Clouds and Voxel Grids.
One of the well-known problems in CNN image classification is that because the CNN classifier sees only a 2D image of the object it won’t recognize that same object if it’s rotated. The solution thus far has been to train on many different orthogonal views of the same object and that vastly expands the problem of training data and training time. Read More
Tag Archives: Image Recognition
These Machine Learning Techniques Make Google Lens A Success
Google Lens was introduced a couple of years ago by Google in a move to spearhead the ‘AI first’ products movement. Now, with the enhancement of machine learning techniques, especially in the domain of image processing and NLP, Google Lens has scaled to new heights. Here we take a look at a few algorithmic based solutions that power up Google Lens:
Lens uses computer vision, machine learning and Google’s Knowledge Graph to let people turn the things they see in the real world into a visual search box, enabling them to identify objects like plants and animals, or to copy and paste text from the real world into their phone. Read More
Cutting-edge research promises to imbue AI with contextual knowledge
Viewing scenes and making sense of them is something people do effortlessly every day. Whether it’s sussing out objects’ colors or gauging their distances apart, it doesn’t take much conscious effort to recognize items’ attributes and apply knowledge to answer questions about them.
That’s patently untrue of most AI systems, which tend to reason rather poorly. But emerging techniques in visual recognition, language understanding, and symbolic program execution promise to imbue them with the ability to generalize to new examples, much like humans. Read More
Efficient Video Generation on Complex Datasets
Generative models of natural images have progressed towards high fidelity samples by the strong leveraging of scale. We attempt to carry this success to the field of video modeling by showing that large Generative Adversarial Networks trained on the complex Kinetics-600 dataset are able to produce video samples of substantially higher complexity than previous work. Our proposed model, Dual Video Discriminator GAN (DVD-GAN), scales to longer and higher resolution videos by leveraging a computationally efficient decomposition of its discriminator. We evaluate on the related tasks of video synthesis and video prediction, and achieve new state of the art Fréchet Inception Distance on prediction for Kinetics-600,as well as state of the art Inception Score for synthesis on the UCF-101 dataset,alongside establishing a strong baseline for synthesis on Kinetics-600. Read More
The AI Renaissance portrait generator isn't great at painting people of color
Surprise! Artificial intelligence-generated portraits based off artwork from 15th century Europe… kind of suck at depicting people of color.
Because we’re apparently always ready to hand over our photos for the sake of a trend, the internet’s current obsession is an AI portrait generator that deconstructs your selfies and rebuilds them as Renaissance and Baroque portraits.
Created by researchers at the MIT-IBM Watson AI Lab, AI Portrait Ars is a fun way to see how you would have been perceived if you lived in another time period.
“Portraits interpret the external beauty, social status, and then go beyond our body and face,” its creators wrote in the site’s “Why” section. “A portrait becomes a psychological analysis and a deep reflection on our existence.”
Unless, apparently, you’re not white. Read More
Facing your AI self at the ‘Neural Mirror’ art installation
Italian design studio Ultravioletto has created a mirror that lets you see yourself the way corporations see you: as a collection of data points. At first, the Neural Mirror installation (located at a former church in the Italian city of Spoleto), seems like an ordinary mirror. But after you’ve been duly scanned and processed (with the system estimating your age, sex and emotional state) you’ll quickly see something else; a ghostly vision of a machine’s idea of who you are. Read More
AI ‘emotion recognition’ can’t be trusted
As artificial intelligence is used to make more decisions about our lives, engineers have sought out ways to make it more emotionally intelligent. That means automating some of the emotional tasks that come naturally to humans — most notably, looking at a person’s face and knowing how they feel.
To achieve this, tech companies like Microsoft, IBM, and Amazon all sell what they call “emotion recognition” algorithms, which infer how people feel based on facial analysis. For example, if someone has a furrowed brow and pursed lips, it means they’re angry. If their eyes are wide, their eyebrows are raised, and their mouth is stretched, it means they’re afraid, and so on.
But the belief that we can easily infer how people feel based on how they look is controversial, and a significant new review of the research suggests there’s no firm scientific justification for it. Read More
Gallery Go: a fast, helpful way to organize your photos offline
Today, at Google for Nigeria we introduced Gallery Go: a photo gallery, designed to work offline, that uses machine learning to automatically organize and make your photos look their best. Gallery Go helps first time smartphone owners easily find, edit, and manage photos, without the need for access to high-speed internet or cloud backup.
Gallery Go automatically organizes your photos by the people and things you take photos of, so you can easily find your favorite selfie, remember where you had the best puff puff, and keep track of important documents. You don’t have to manually label your photos and all these features run on your phone, without using your data. You can create folders to organize your photos, and Gallery Go works with SD cards, so you can easily copy them from your phone. Read More
This AI magically removes moving objects from videos
We’ve previously seen developers harness the power of artificial intelligence (AI) to turn pitch black pics into bright colorful photos, flat images into complex 3D scenes, and selfies into moving avatars. Now, there’s an AI-powered software that effortlessly removes moving objects from videos.
All you need to do to wipe an object from footage is draw a box around it, and the software takes care of the rest for you. Read More
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