SiamRPN-TF

This repository includes a tensorflow implementation of SiamRPN[1]
The best AUC score on OTB100 of this repository so far: 0.602 （the AUC score in the paper[1] is 0.637)

Some differences between this repository and SiamRPN

less training videos(unable to download YouTube-BB :dizzy_face:...)
- DET2014+VID2015+LASOT+GOT10k(about 20k videos)
- SiamRPN[1] use YouTube-BB+VID2015（about 100k videos)
more data augmentation
- random mixup [2]
- random image blur & color jittering

Add more details ... (TODO)

Training dataset is more important than anything else
Use pretrained feature extraction and train the network from deep layer to shallow layer step by step
- first train deeper layers with larger learning rate
- and then train the whole network with smaller learning rate
Models trained from scratch always perform worse (best AUC score on OTB100: 0.564) in my experiment even with longer training time(5 times), this might be attributed to limited training dataset

[ ] Achieve the AUC score in the paper[1]
[ ] To speed up training by replace tf.py_func & numpy operation with pure tf implementation
[x] Multi-GPU Training & load dataset with lmdb lmdb dataset download(about 120G) code: dn58
[x] Convert pytorch pretrained model to initialize embedding function
[x] learning rate warmup
[x] Train network with static images and dynamic videos
[x] Add time decay option to weight loss[3] (a slight improvement)
[x] Add random Mixup[2]

[1] High Performance Visual Tracking With Siamese Region Proposal Network (CVPR 2018)

[2] Bag of Freebies for Training Object Detection Neural Networks

[3] Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking