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Balancing Specialization, Generalization, and Compression for Detection
  and Tracking

Balancing Specialization, Generalization, and Compression for Detection and Tracking

25 September 2019
Dotan Kaufman
Koby Bibas
Eran Borenstein
Michael Chertok
Tal Hassner
    MQ
ArXivPDFHTML

Papers citing "Balancing Specialization, Generalization, and Compression for Detection and Tracking"

7 / 7 papers shown
Title
Deep pNML: Predictive Normalized Maximum Likelihood for Deep Neural
  Networks
Deep pNML: Predictive Normalized Maximum Likelihood for Deep Neural Networks
Koby Bibas
Yaniv Fogel
M. Feder
BDL
45
19
0
28 Apr 2019
Precise Detection in Densely Packed Scenes
Precise Detection in Densely Packed Scenes
Eran Goldman
Roei Herzig
Aviv Eisenschtat
Oria Ratzon
Itsik Levi
Jacob Goldberger
Tal Hassner
51
187
0
01 Apr 2019
Online Multi-Object Tracking Using CNN-based Single Object Tracker with
  Spatial-Temporal Attention Mechanism
Online Multi-Object Tracking Using CNN-based Single Object Tracker with Spatial-Temporal Attention Mechanism
Qi Chu
Wanli Ouyang
Hongsheng Li
Xiaogang Wang
Bin Liu
Nenghai Yu
VOT
48
347
0
09 Aug 2017
CREST: Convolutional Residual Learning for Visual Tracking
CREST: Convolutional Residual Learning for Visual Tracking
Yibing Song
Chao Ma
Lijun Gong
Jiawei Zhang
Rynson W. H. Lau
Ming-Hsuan Yang
70
487
0
01 Aug 2017
Channel Pruning for Accelerating Very Deep Neural Networks
Channel Pruning for Accelerating Very Deep Neural Networks
Yihui He
Xiangyu Zhang
Jian Sun
196
2,521
0
19 Jul 2017
R-FCN: Object Detection via Region-based Fully Convolutional Networks
R-FCN: Object Detection via Region-based Fully Convolutional Networks
Jifeng Dai
Yi Li
Kaiming He
Jian Sun
ObjD
158
5,635
0
20 May 2016
Learning both Weights and Connections for Efficient Neural Networks
Learning both Weights and Connections for Efficient Neural Networks
Song Han
Jeff Pool
J. Tran
W. Dally
CVBM
296
6,660
0
08 Jun 2015
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