This week we implemented the evaluation metrics(Intersection over Union (IoU) and mean Average Precision (mAP)) that have been used in all tasks again.
[IoU with noise DB ]
[mAP with noise DB ]
The main task is to use Gaussian models to model the background pixels of the video sequence to classify them as background / foreground.
[bbox_adaptive]
Object Detection Mask-RCNN framework with ResNet-101 as the backbone
[Mask-RCNN]
[Faster-RCNN]
[Optical Flow]
[Video Stabilization]
[Result of Multi-target multi-camera tracking through Color Histogram + metric learning]
Slides of week5
Technical report
Member | |
---|---|
Yixiong Yang | yangyxwork@163.com |
Sanket Biswas | sanket.biswas@e-campus.uab.cat |
Gabriela Cordova | gabrielaelizabeth.cordova@e-campus.uab.cat |
Marc Oros Casanas | marc.oros@e-campus.uab.cat |
Keyao Li | keyao.li@e-campus.uab.cat |