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ECCV 2018 Triplet Loss in Siamese Network for Object Tracking
This project forked from seafishzha/triplettracking
ECCV 2018 Triplet Loss in Siamese Network for Object Tracking
Implementation code for eccv 2018: [1] X. Dong and J. Shen Triplet loss in siamese network for object tracking, ECCV, pp. 459-474, 2018 ======================================================================== Any comments, please email: [email protected] [email protected] This software was developed under Ubuntu 14.04 with matlab 2017a. If you use this software for academic research, please cite the following paper: @inproceedings{dong2018triplet, title={Triplet loss in siamese network for object tracking}, author={Dong, Xingping and Shen, Jianbing}, booktitle={Proceedings of the European Conference on Computer Vision (ECCV)}, pages={459--474}, year={2018} } [**Prerequisites**] Cuda 7.5 cuDNN v5.1 Matconvnet v1.0-beta20 Matlab 2017a [**Training**] After you finish all Prerequisites, you can train our network step by step. 1. Perpare dataset: (same instructions in SiamFC:'Fully-Convolutional Siamese Networks for Object Tracking' ) Follow these [step-by-step instructions] in ./ILSVRC15-curation/README.md 2. Setup the paths in ./training/env_paths_training.m and startup.m 3. Run the script for training: ./training/run_experiment_tri.m 4. After training, you can select the epoch with the lowest val errdisp according ./training/triplet_gray/net-train.pdf (net-epoch-1.mat in this test code). Then this model can be used for tracking in next step. [**Tracking**] 1. You can directly run './tracking/demo.m' as a demo to test our algrithom with the pre-trained model ('./models/triplet.net.mat'). You can also try your trained model by modifying ./tracking/run_tracker.m and env_paths_tracking.m. Note: some codes are borrow from "SiamFC". Thanks for all authors of SiamFC.
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