- Ubuntu 18.04, python 3.8, A100
- PyTorch 1.8.1 + CUDA 11.1
bash ./download.sh
then the files will be downloaded and saved in the following folders:
pittsburgh
├── database
├── query
├── structure
logs
├── student_contrast
├── student_quadruplet
├── student_triplet
├── teacher_triplet
-
STUN
python main.py --resume=logs/student_triplet/ckpt.pth.tar
-
STUN (Constrast)
python main.py --resume=logs/student_constrast/ckpt.pth.tar
-
STUN (Quadruplet)
python main.py --resume=logs/student_quadruplet/ckpt.pth.tar
-
Standard Triplet
python main.py --phase=test_tea --resume=logs/teacher_triplet/ckpt.pth.tar
python vis_results.py
# you can plot results of different models by populate the NETWORK variable.
r@1/5/10 ↑ | mAP@1/5/10 ↑ | AP ↑ | ECE{r@1/5/10}↓ | ECE{mAP@1/5/10}↓ | ECE{AP}↓ | |
---|---|---|---|---|---|---|
Standard Triplet | 0.548 / 0.802 / 0.877 | 0.548 / 0.268 / 0.167 | 0.678 | - | - | - |
MC Dropout | 0.302 / 0.523 / 0.611 | 0.302 / 0.108 / 0.061 | 0.463 | 0.205 / 0.075 / 0.112 | 0.205 / 0.396 / 0.443 | 0.111 |
PFE w/o MLS | 0.550 / 0.805 / 0.876 | 0.550 / 0.266 / 0.167 | 0.690 | 0.413 / 0.160 / 0.092 | 0.413 / 0.695 / 0.795 | 0.275 |
PFE w/ MLS | 0.444 / 0.680 / 0.764 | 0.444 / 0.199 / 0.120 | 0.655 | 0.517 / 0.284 / 0.200 | 0.517 / 0.762 / 0.841 | 0.336 |
BTL | 0.515 / 0.766 / 0.840 | 0.515 / 0.252 / 0.158 | 0.591 | 0.236 / 0.058 / 0.105 | 0.236 / 0.497 / 0.591 | 0.131 |
Ours: STUN | 0.613 / 0.840 / 0.898 | 0.613 / 0.280 / 0.171 | 0.739 | 0.171 / 0.084 / 0.127 | 0.171 / 0.491 / 0.600 | 0.067 |
Ours: STUN (Contrastive) | 0.512 / 0.767 / 0.845 | 0.512 / 0.204 / 0.119 | 0.610 | 0.185 / 0.086 / 0.152 | 0.185 / 0.493 / 0.577 | 0.054 |
Ours: STUN (Quadruplet) | 0.625 / 0.846 / 0.902 | 0.625 / 0.294 / 0.180 | 0.740 | 0.114 / 0.140 / 0.194 | 0.114 / 0.412 / 0.524 | 0.072 |