The winning team of researchers is a Dream Team of experts from Massachusetts Institute of Technology and the Boston University. It includes experts in neuroscience, robotics, computer science, computer vision, artificial intelligence, mathematical systems theory, and a host of other related advanced technology domains.

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have come up with a way to get a better handle on this understanding of complex motion. 

The new system uses an algorithm that can take 2-D videos and turn them into 3-D-printed “motion sculptures” that show how a human body moves through space.

We present Dense Object Nets, which build on recent developments in self-supervised dense descriptor learning, as a consistent object representation for visual understanding and manipulation.

MIT researchers describe an autonomous system for a fleet of drones to collaboratively search under dense forest canopies. The drones use only onboard computation and wireless communication — no GPS required.

We present a novel computational framework for high-resolution topology optimization that delivers leaps in simulation capabilities, by two orders of magnitude, from the state-of-the-art approaches.

The RePaint system reproduces paintings by combining two approaches called color-contoning and half-toning, as well as a deep learning model focused on determining how to stack 10 different inks to recreate the specific shades of color.

As the largest publicly available collection of recipe data, Recipe1M affords the ability to train high capacity models on aligned, multi-modal data.

From a single image, humans are able to perceive the full 3D shape of an object by exploiting learned shape priors from everyday life. Contemporary single-image 3D reconstruction algorithms aim to solve this task in a similar fashion, but often end up with priors that are highly biased by training classes.

Amateur and professional musicians alike may spend hours pouring over YouTube clips to figure out exactly how to play certain parts of their favorite songs. But what if there were a way to play a video and isolate the only instrument you wanted to hear?