update readme

README.md

@@ -39,6 +39,8 @@ These two classes are used for [torch.utils.data.DataLoader](http://pytorch.org/
 * `xent`: cross entropy + label smoothing regularizer [5].
 * `htri`: triplet loss with hard positive/negative mining [4] .
 
+We use `Adam` [6] everywhere, which turned out to be the most effective optimizer in our experiments.
+
 ## Train
 Training codes are implemented mainly in
 * `train_img_model_xent.py`: train image model with cross entropy loss.
@@ -88,7 +90,6 @@ python train_vid_model_xent.py -d mars -a resnet50 --evaluate --resume saved-mod
 ```
 Note that `--test-batch` in video reid represents number of tracklets. If we set this argument to 2, and sample 15 images per tracklet, the resulting number of images per batch is 2*15=30. Adjust this argument according to your GPU memory.
 
-
 ## References
 [1] [He et al. Deep Residual Learning for Image Recognition. CVPR 2016.](https://arxiv.org/abs/1512.03385)<br />
 [2] [Yu et al. The Devil is in the Middle: Exploiting Mid-level Representations for Cross-Domain Instance Matching. arXiv:1711.08106.](https://arxiv.org/abs/1711.08106) <br />