We present a method for the detection of instances of an
object class, such as cars or pedestrians, in natural images.
Similarly to some previous works, this is accomplished via
...
We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure" model. The 3D shape of an object class is represented by sets...
Kristen Grauman, Gregory Shakhnarovich, Trevor Dar...
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
Contextual text mining is concerned with extracting topical themes from a text collection with context information (e.g., time and location) and comparing/analyzing the variations...
We continue the investigation of locally testable codes, i.e., error-correcting codes for whom membership of a given word in the code can be tested probabilistically by examining ...