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Unsupervised Discovery of Action Classes

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/11585978_14openalex-snapshot
Linear Programming Matching and Appearance-Adaptive Object Tracking
inferredcites →https://doi.org/10.1007/3-540-47969-4_42openalex-snapshot
Recognizing and Tracking Human Action
inferredcites →https://doi.org/10.1007/978-94-015-8935-2openalex-snapshot
Motion-Based Recognition
inferredcites →https://doi.org/10.1023/a:1007975200487openalex-snapshot
Detection and Recognition of Periodic, Nonrigid Motion
inferredcites →https://doi.org/10.1023/a:1020350100748openalex-snapshot
View-Invariant Representation and Recognition of Actions
inferredcites →https://doi.org/10.1109/34.868681openalex-snapshot
Robust real-time periodic motion detection, analysis, and applications
inferredcites →https://doi.org/10.1109/34.868688openalex-snapshot
Normalized cuts and image segmentation
inferredcites →https://doi.org/10.1109/34.910878openalex-snapshot
The recognition of human movement using temporal templates
inferredcites →https://doi.org/10.1109/34.993558openalex-snapshot
Shape matching and object recognition using shape contexts
inferredcites →https://doi.org/10.1109/cvpr.2004.1315249openalex-snapshot
Detecting unusual activity in video
inferredcites →https://doi.org/10.1109/cvpr.2004.1315253openalex-snapshot
Names and faces in the news
inferredcites →https://doi.org/10.1109/event.2001.938872openalex-snapshot
Hierarchical unsupervised learning of facial expression categories
inferredcites →https://doi.org/10.1109/iccv.1999.791201openalex-snapshot
Exploiting human actions and object context for recognition tasks
inferredcites →https://doi.org/10.1109/iccv.1999.791202openalex-snapshot
Real-time object detection for "smart" vehicles
inferredcites →https://doi.org/10.1109/iccv.2005.142openalex-snapshot
Learning object categories from Google's image search
inferredcites →https://doi.org/10.1109/iccv.2005.248openalex-snapshot
Video behaviour profiling and abnormality detection without manual labelling
inferredcites →https://doi.org/10.1109/iccv.2005.70openalex-snapshot
Detecting irregularities in images and in video
inferredcites →https://doi.org/10.1109/iccv.2005.77openalex-snapshot
Discovering objects and their location in images
inferredcites →https://doi.org/10.1109/tpami.2005.220openalex-snapshot
Efficient shape matching using shape contexts

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/9781118219546.refsopenalex-snapshot
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Databases used for still image-based action recognition
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Action4D: Real-time Action Recognition in the Crowd and Clutter
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Computer Science & Information Technology (CS & IT)
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Basketball-51: A Video Dataset for Activity Recognition in the Basketball Game
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Motion Prediction Using Depth Information of Human Arm Based on Alexnet
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HUMAN ACTION POSELETS ESTIMATION VIA COLOR G-SURF IN STILL IMAGES
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Human Action Recognition and Prediction for Robotics Applications
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