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 appearance based classifiers. In this work, we are interested in understanding the roles of these different tasks in improved scene understanding, in particular semantic segmentation, object detection and scene recognition. Towards this goal, we “plug-in” human subjects for each of the various components in a state-of-the-art conditional random field model. Comparisons among various hybrid human-machine CRFs give us indications of how much “head room” there is to improve scene understanding by focusing research efforts on ...
For the challenging semantic image segmentation task the best performing models have traditionally c...
We seek to both detect and segment objects in images. To exploit both local image data as well as co...
International audienceConditional Random Fields (CRFs) are an effective tool for a variety of differ...
Abstract—Recent trends in image understanding have pushed for scene understanding models that jointl...
Recent trends in semantic image segmentation have pushed for holistic scene understanding models tha...
Scene understanding is one of the holy grails of computer vision. Despite decades of research on sce...
In this thesis we exploit the generality and expressive power of the Associative Hierarchical Random...
In this paper, a new framework for scene understanding using multi-modal high-ordered context-model ...
Perceiving 3D structure and recognizing objects and their properties around us is central to our und...
Although humans can effortlessly recognise a scene in its totality, it is an extremely challenging p...
Intelligent robots require advanced vision capabilities to perceive and interact with the real physi...
(c) 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for...
One aim of holistic image understanding is not only to recognise the things and stuff in images but ...
Scene understanding, including object recognition, is perhaps the most challenging task in computer ...
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer S...
For the challenging semantic image segmentation task the best performing models have traditionally c...
We seek to both detect and segment objects in images. To exploit both local image data as well as co...
International audienceConditional Random Fields (CRFs) are an effective tool for a variety of differ...
Abstract—Recent trends in image understanding have pushed for scene understanding models that jointl...
Recent trends in semantic image segmentation have pushed for holistic scene understanding models tha...
Scene understanding is one of the holy grails of computer vision. Despite decades of research on sce...
In this thesis we exploit the generality and expressive power of the Associative Hierarchical Random...
In this paper, a new framework for scene understanding using multi-modal high-ordered context-model ...
Perceiving 3D structure and recognizing objects and their properties around us is central to our und...
Although humans can effortlessly recognise a scene in its totality, it is an extremely challenging p...
Intelligent robots require advanced vision capabilities to perceive and interact with the real physi...
(c) 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for...
One aim of holistic image understanding is not only to recognise the things and stuff in images but ...
Scene understanding, including object recognition, is perhaps the most challenging task in computer ...
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer S...
For the challenging semantic image segmentation task the best performing models have traditionally c...
We seek to both detect and segment objects in images. To exploit both local image data as well as co...
International audienceConditional Random Fields (CRFs) are an effective tool for a variety of differ...