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Found 6 papers, 2 papers with code
Visual Enumeration is Challenging for Large-scale Generative AI
Humans can readily judge the number of objects in a visual scene, even without counting, and such a skill has been documented in many animal species and babies prior to language development and formal schooling.
Investigating the generative dynamics of energy-based neural networks
Generative neural networks can produce data samples according to the statistical properties of their training distribution.
A developmental approach for training deep belief networks
Deep belief networks (DBNs) are stochastic neural networks that can extract rich internal representations of the environment from the sensory data.
On the difficulty of learning and predicting the long-term dynamics of bouncing objects
In recent years, a variety of approaches have been proposed for learning to predict the physical dynamics of objects interacting in a visual scene.
Perception of visual numerosity in humans and machines
Numerosity perception is foundational to mathematical learning, but its computational bases are strongly debated.
Robust Large-Scale Localization in 3D Point Clouds Revisited
We tackle the problem of getting a full 6-DOF pose estimation of a query image inside a given point cloud.
