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使用深度强化学习进行多目标跟踪

License: Apache License 2.0

MATLAB 42.84% C++ 13.72% Cuda 14.52% C 2.58% Shell 0.31% M 0.08% Java 18.66% HTML 0.50% Objective-C 0.02% Python 6.77%

deep-reinforcement-learning visual-tracking

visualtracking_drl's Introduction

Multi-Object Tracking Use Deep Reinforcement Learning

ADNet: Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning [Paper]
[Project Page]
MDP_Tracking: Learning to Track: Online Multi-Object Tracking by Decision Making
[Project Page]
Email: [email protected] [main page]

Install

Test on (ubuntu 14.04 and ubuntu 16.04) 64bit, MATLAB 2017a and MATLAB 2018a, use Cuda-8.0 and NVIDIA GTX 1080 TI.
Run adnet_compile.m to compile MatConvNet.
modify train data path: utils/get_benchmark_path.m
'models/imagenet-vgg-m-conv1-3.mat' copy from [MDNet]

Run tracking

run adnet_demo.m.

Other

[[ADNet]] 0.646 0.880
[DRLT] 0.635
[DRL-IS] 0.671 0.909
[MDNet] 0.678 0.909
[SANet] 0.661 0.913
[ECO] 0.691 0.910
[CFNet]

Prospect

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hell-to-heaven is-repo

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