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- Carnegie Mellon UniversityUS49 papers
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5 papers · 2 filters
Learning a Complete Image Indexing Pipeline
Himalaya Jain, Joaquin Zepeda, Patrick Pérez +1
To work at scale, a complete image indexing system comprises two components: An inverted file index to restrict the actual search to only a subset that should contain most of the i…
Compressed Video Action Recognition
Chao-Yuan Wu, Manzil Zaheer, Hexiang Hu +3
Training robust deep video representations has proven to be much more challenging than learning deep image representations. This is in part due to the enormous size of raw video st…
Embedding Visual Hierarchy with Deep Networks for Large-Scale Visual Recognition
Tianyi Zhao, Baopeng Zhang, Wei Zhang +3
In this paper, a level-wise mixture model (LMM) is developed by embedding visual hierarchy with deep networks to support large-scale visual recognition (i.e., recognizing thousands…
Temporal Segment Networks for Action Recognition in Videos
Limin Wang, Yuanjun Xiong, Zhe Wang +4
Deep convolutional networks have achieved great success for image recognition. However, for action recognition in videos, their advantage over traditional methods is not so evident…
Scatteract: Automated extraction of data from scatter plots
Mathieu Cliche, David Rosenberg, Dhruv Madeka +1
Charts are an excellent way to convey patterns and trends in data, but they do not facilitate further modeling of the data or close inspection of individual data points. We present…