We combine methods from computer science, neuroscience and cognitive science to explain and model how perception and cognition are realized in human and machine.
Our research in computational neuroscience, cognitive computing and computer vision, ranges from theory to experiments to applications, accelerating the rate at which discoveries are made by solving problems through a multi-disciplinary way of thinking. Science and technology is at the threshold of paradigm-shifting discoveries. However, an obstacle remains: as technology grows exponentially, our understanding of the human mind does not. We are approaching an era in which the benefits of a highly technologized society won’t be fully realized unless we are able to understand how humans encode, process, retain, predict and imagine.
Using a new software technology combining the strengths of MEG (magneto-encephalography) and fMRI (functional magnetic resonance imaging), we are able to characterize the spatiotemporal dynamics of perceived or imagined events at the level of the whole human brain.
Moments is a large-scale human-annotated dataset of ~ 1 million (and growing) labelled videos corresponding to real-world actions, motions and events unfolding within three seconds.
Researchers use synthetic data to improve a model’s ability to grasp conceptual information, which could enhance automatic captioning and question-answering systems.
Models trained on synthetic data can be more accurate than other models in some cases, which could eliminate some privacy, copyright, and ethical concerns from using real data.
Sometimes it’s easy to forget how good we humans are at understanding our surroundings. Without much thinking, we can describe objects and how they interact with each other.
