We propose to bridge the gap between Random Field (RF) formulations for joint categorization and segmentation (JCaS), which model local interactions among pixels and superpixels, ...
Current face image retrieval methods achieve impressive results, but lack efficient ways to refine the search, particularly for geometric face attributes. Users cannot easily ...
In this paper, we design a novel MRF framework which is called Non-Local Range Markov Random Field (NLRMRF). The local spatial range of clique in traditional MRF is extended to th...
Objects vary in their visual complexity, yet existing discovery methods perform “batch” clustering, paying equal attention to all instances simultaneously—regardless of the ...
The goal of object category discovery is to automatically identify groups of image regions which belong to some new, previously unseen category. This task is typically performed i...
Carolina Galleguillos, Brian McFee, Serge Belongie...
Cosegmentation is typically defined as the task of jointly segmenting “something similar” in a given set of images. Existing methods are too generic and so far have not demon...
Supervised methods for learning an embedding aim to map high-dimensional images to a space in which perceptually similar observations have high measurable similarity. Most approac...
Graham Taylor, Ian Spiro, Rob Fergus, Christoph Br...
We describe a generative model of the relationship between two images. The model is defined as a factored threeway Boltzmann machine, in which hidden variables collaborate to de...
Joshua Susskind, Roland Memisevic, Geoffrey Hinton...
We describe an imaging architecture for compressive video sensing termed programmable pixel compressive camera (P2C2). P2C2 allows us to capture fast phenomena at frame rates high...
Visual attributes expose human-defined semantics to object recognition models, but existing work largely restricts their influence to mid-level cues during classifier training....