Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking
ArTIST
Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking (CVPR 2021)
Pytorch implementation of the ArTIST motion model. In this repo, there are
- Training script for the Moving Agent network
- Training script for the ArTIST motion model
- Demo script for Inferring the likelihood of current observations (detections)
- Demo script for Inpainting the missing observation/detections
Demo 1: Likelihood estimation of observation
Run:
python3 demo_scoring.py
This will generate the output in the temp/ar/log_p directory, look like this:
This demo gets as input a pretrained model of the Moving Agent Network (MA-Net), a pretrained model of ArTIST, the centroids (obtain centroids via the script in the utils), a demo test sample index and the number of clusters.
The model then evaluates