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AGI
2011
14 years 10 months ago
Systematically Grounding Language through Vision in a Deep, Recurrent Neural Network
Human intelligence consists largely of the ability to recognize and exploit structural systematicity in the world, relating our senses simultaneously to each other and to our cogni...
Derek Monner, James A. Reggia
ACL
2012
13 years 9 months ago
Hierarchical Chunk-to-String Translation
We present a hierarchical chunk-to-string translation model, which can be seen as a compromise between the hierarchical phrasebased model and the tree-to-string model, to combine ...
Yang Feng, Dongdong Zhang, Mu Li, Qun Liu
CVPR
2009
IEEE
17 years 1 months ago
Towards Total Scene Understanding: Classification, Annotation and Segmentation in an Automatic Framework
Given an image, we propose a hierarchical generative model that classifies the overall scene, recognizes and segments each object component, as well as annotates the image with ...
Fei-Fei Li 0002, Li-Jia Li, Richard Socher
CVPR
2009
IEEE
17 years 1 months ago
A Multi-View Probabilistic Model for 3D Object Classes
We propose a novel probabilistic framework for learning visual models of 3D object categories by combining appearance information and geometric constraints. Objects are represen...
Fei-Fei Li 0002, Hao Su, Min Sun, Silvio Savarese
CVPR
2006
IEEE
16 years 8 months ago
A Design Principle for Coarse-to-Fine Classification
Coarse-to-fine classification is an efficient way of organizing object recognition in order to accommodate a large number of possible hypotheses and to systematically exploit shar...
Sachin Gangaputra, Donald Geman