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» Annotator Rationales for Visual Recognition
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CVPR
2012
IEEE
11 years 10 months ago
Discovering localized attributes for fine-grained recognition
Attributes are visual concepts that can be detected by machines, understood by humans, and shared across categories. They are particularly useful for fine-grained domains where c...
Kun Duan, Devi Parikh, David J. Crandall, Kristen ...
COMPSYSTECH
2010
13 years 6 months ago
Anthropocentric video analysis for film and games postproduction
: The interest of the scientific community for anthropocentric (human-centered) video analysis stems from the fact that the extracted information (e.g. human presence, identity, bo...
Ioannis Pitas, Nikolaos Nikolaidis
CVPR
2008
IEEE
14 years 9 months ago
Learning realistic human actions from movies
The aim of this paper is to address recognition of natural human actions in diverse and realistic video settings. This challenging but important subject has mostly been ignored in...
Ivan Laptev, Marcin Marszalek, Cordelia Schmid, Be...
CVPR
2011
IEEE
13 years 4 months ago
Interactively Building a Discriminative Vocabulary of Nameable Attributes
Human-nameable visual attributes offer many advantages when used as mid-level features for object recognition, but existing techniques to gather relevant attributes can be ineffici...
Devi Parikh, Kristen Grauman
MIR
2005
ACM
141views Multimedia» more  MIR 2005»
14 years 1 months ago
A mutual semantic endorsement approach to image retrieval and context provision
Learning semantics from annotated images to enhance content-based retrieval is an important research direction. In this paper, annotation data are assumed available for only a sub...
Jia Li