Now showing items 1-4 of 4
Human-Machine CRFs for Identifying Bottlenecks in Holistic Scene Understanding
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-06-15)
Recent trends in image understanding have pushed for holistic scene understanding models that jointly reason about various tasks such as object detection, scene recognition, shape analysis, contextual reasoning, and local ...
A role for recurrent processing in object completion: neurophysiological, psychophysical and computational evidence.
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-04-26)
Recognition of objects from partial information presents a significant challenge for theories of vision because it requires spatial integration and extrapolation from prior knowledge. We combined neurophysiological recordings ...
Parsing Semantic Parts of Cars Using Graphical Models and Segment Appearance Consistency
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-06-13)
This paper addresses the problem of semantic part parsing (segmentation) of cars, i.e.assigning every pixel within the car to one of the parts (e.g.body, window, lights, license plates and wheels). We formulate this as a ...
Seeing is Worse than Believing: Reading People’s Minds Better than Computer-Vision Methods Recognize Actions
We had human subjects perform a one-out-of-six class action recognition task from video stimuli while undergoing functional magnetic resonance imaging (fMRI). Support-vector machines (SVMs) were trained on the recovered ...