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3D

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Seeing The Whole From Some Of The Parts

Upon looking at photographs and drawing on their past experiences, humans can often perceive depth in pictures that are, themselves, perfectly flat. However, getting computers to do the same thing has proved quite challenging. The problem is difficult for several reasons, one being that information is inevitably lost when a scene that takes place in three dimensions is reduced to a two-dimensional (2D) representation. There are some well-established strategies for recovering 3D information from multiple 2D images, but they each have some limitations. A new approach called “virtual correspondence,” which was developed by researchers at MIT and other institutions, can…
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An Easier Way To Teach Robots New Skills

With e-commerce orders pouring in, a warehouse robot picks mugs off a shelf and places them into boxes for shipping. Everything is humming along, until the warehouse processes a change and the robot must now grasp taller, narrower mugs that are stored upside down. Reprogramming that robot involves hand-labeling thousands of images that show it how to grasp these new mugs, then training the system all over again. But a new technique developed by MIT researchers would require only a handful of human demonstrations to reprogram the robot. This machine-learning method enables a robot to pick up and place never-before-seen…
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Simplifying 3D Understanding Using Self-Supervised Learning And Transformers

Pretraining using large labeled data sets has become a core tool for developing high-performance computer vision (CV) models. But while this method works well with many types of media, it hasn’t been widely used for 3D recognition tasks, such as identifying and localizing a couch in a 3D scan of a living room. This is due to a lack of annotated data and the time-consuming nature of labeling 3D data sets. Additionally, models for 3D understanding often rely on a handcrafted architecture design that is tightly coupled with the particular 3D data set used for training. At ICCV 2021, we…
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Bring Iconic Japanese Characters To Life With AR In Search

We all need a bit of escapism sometimes, and there’s nothing like a blast from the pop-culture past to do the trick. Today, we’re bringing characters from classic Japanese anime, games and TV shows to life — from Pac-Man to Hello Kitty — with augmented reality (AR) in Search. Japan’s anime and video game culture emerged between the 1950s and the 1980s, as comic books, gaming arcades and home TVs and consoles boomed. But it wasn’t just a Japanese phenomenon. The most iconic characters caught people’s imaginations around the world, and they’re still hugely popular today. Which animated icon is…
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AI Mirrors The Way Human Brains See In 3D

Researchers have discovered characteristics of human 3D vision in a computer vision network only designed to “view” in 2D. The brain detects 3D shape fragments such as bumps, hollows, shafts, and spheres in the beginning stages of object vision—a newly discovered strategy of natural intelligence. The researchers found that same strategy in artificial intelligence networks trained to recognize visual objects. “…I never would have guessed in a million years that you would see the same thing happening in Alexnet, which is only trained to translate 2D photographs into object labels.” Their new paper in Current Biology details how neurons in area V4,…
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