We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Recent studies show that state-space dynamics of randomly initialized recurrent neural network (RNN) has interesting and potentially useful properties even without training. More p...
Psychological experiments on children's development of spatial knowledge suggest experience at self-locomotion with visual tracking as important factors. Yet, the mechanism u...
This paper presents an efficient and scalable coding scheme for transmitting a stream of 3D models extracted from a video. As in classical model-based video coding, the geometry, ...
We propose a new method to quickly and accurately predict 3D positions of body joints from a single depth image, using no temporal information. We take an object recognition appro...
Jamie Shotton, Andrew Fitzgibbon, Mat Cook, Andrew...