Title
HNIP: Compact Deep Invariant Representations for Video Matching, Localization, and Retrieval.
Abstract
With emerging demand for large-scale video analysis, MPEG initiated the compact descriptor for video analysis (CDVA) standardization in 2014. Beyond handcrafted descriptors adopted by the current MPEG-CDVA reference model, we study the problem of deep learned global descriptors for video matching, localization, and retrieval. First, inspired by a recent invariance theory, we propose a nested invar...
Year
DOI
Venue
2017
10.1109/TMM.2017.2713410
IEEE Transactions on Multimedia
Keywords
Field
DocType
Transform coding,Encoding,Feature extraction,Robustness,Standards,Visualization,Image coding
Reference model,Convolutional neural network,Computer science,Robustness (computer science),Artificial intelligence,Computer vision,Pattern recognition,Visualization,Pooling,Transform coding,Feature extraction,Machine learning,Encoding (memory)
Journal
Volume
Issue
ISSN
19
9
1520-9210
Citations 
PageRank 
References 
3
0.38
43
Authors
9
Name
Order
Citations
PageRank
Jie Lin13495502.80
Ling-yu Duan21770124.87
Shiqi Wang31281120.37
yan bai4567.60
Lou Yihang5759.57
Vijay Chandrasekhar619122.83
Tiejun Huang71281120.48
Alex ChiChung Kot833527.20
Wen Gao911374741.77