Computer vision

A flexible solution to help artists improve animation

Artists who bring to life heroes and villains in animated movies and video games could have more control over their animations, thanks to a new technique introduced by MIT researchers. Their method generates mathematical functions known as barycentric coordinates, which define how 2D and 3D shapes can bend, stretch, and move through space. For example, an artist using their tool…

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A computer scientist pushes the boundaries of geometry

More than 2,000 years ago, the Greek mathematician Euclid, known to many as the father of geometry, changed the way we think about shapes. Building off those ancient foundations and millennia of mathematical progress since, Justin Solomon is using modern geometric techniques to solve thorny problems that often seem to have nothing to do with shapes. For instance, perhaps a…

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Synthetic imagery sets new bar in AI training efficiency

Data is the new soil, and in this fertile new ground, MIT researchers are planting more than just pixels. By using synthetic images to train machine learning models, a team of scientists recently surpassed results obtained from traditional “real-image” training methods. At the core of the approach is a system called StableRep, which doesn't just use any synthetic images; it…

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From physics to generative AI: An AI model for advanced pattern generation

Generative AI, which is currently riding a crest of popular discourse, promises a world where the simple transforms into the complex — where a simple distribution evolves into intricate patterns of images, sounds, or text, rendering the artificial startlingly real. The realms of imagination no longer remain as mere abstractions, as researchers from MIT's Computer Science and Artificial Intelligence Laboratory…

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Multi-AI collaboration helps reasoning and factual accuracy in large language models

An age-old adage, often introduced to us during our formative years, is designed to nudge us beyond our self-centered, nascent minds: "Two heads are better than one." This proverb encourages collaborative thinking and highlights the potency of shared intellect. Fast forward to 2023, and we find that this wisdom holds true even in the realm of artificial intelligence: Multiple language…

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Helping computer vision and language models understand what they see

Powerful machine-learning algorithms known as vision and language models, which learn to match text with images, have shown remarkable results when asked to generate captions or summarize videos. While these models excel at identifying objects, they often struggle to understand concepts, like object attributes or the arrangement of items in a scene. For instance, a vision and language model might…

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MIT researchers combine deep learning and physics to fix motion-corrupted MRI scans

Compared to other imaging modalities like X-rays or CT scans, MRI scans provide high-quality soft tissue contrast. Unfortunately, MRI is highly sensitive to motion, with even the smallest of movements resulting in image artifacts. These artifacts put patients at risk of misdiagnoses or inappropriate treatment when critical details are obscured from the physician. But researchers at MIT may have developed…

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Using AI to protect against AI image manipulation

As we enter a new era where technologies powered by artificial intelligence can craft and manipulate images with a precision that blurs the line between reality and fabrication, the specter of misuse looms large. Recently, advanced generative models such as DALL-E and Midjourney, celebrated for their impressive precision and user-friendly interfaces, have made the production of hyper-realistic images relatively effortless.…

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Computer vision system marries image recognition and generation

Computers possess two remarkable capabilities with respect to images: They can both identify them and generate them anew. Historically, these functions have stood separate, akin to the disparate acts of a chef who is good at creating dishes (generation), and a connoisseur who is good at tasting dishes (recognition). Yet, one can’t help but wonder: What would it take to…

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Researchers use AI to identify similar materials in images

A robot manipulating objects while, say, working in a kitchen, will benefit from understanding which items are composed of the same materials. With this knowledge, the robot would know to exert a similar amount of force whether it picks up a small pat of butter from a shadowy corner of the counter or an entire stick from inside the brightly…

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Making property assessments as simple as snapping a picture

Property assessments sit at the center of home appraisals, insurance claims, renovation projects, and a number of other important processes. Inaccurate or delayed assessments can set projects back and stick consumers with higher costs. Now, a platform first developed at MIT makes creating detailed property assessments as easy as snapping a few pictures. The alumni-founded startup Hosta a.i. analyzes images…

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Training machines to learn more like humans do

Imagine sitting on a park bench, watching someone stroll by. While the scene may constantly change as the person walks, the human brain can transform that dynamic visual information into a more stable representation over time. This ability, known as perceptual straightening, helps us predict the walking person’s trajectory. Unlike humans, computer vision models don’t typically exhibit perceptual straightness, so…

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