Hello @aman_goyal ,
If I understand correctly, you can extract provided model backbone weights by the following codes:
import torch
model = torch.load('qdtrack-frcnn_r50_fpn_12e_bdd100k-13328aed.pth')
new_state_dict = {}
for name, weight in model['state_dict'].items():
    if 'backbone' in name:
        new_state_dict[name] = weight

This new state dict contains the end-to-end trained weights.  you can create a new model with this state dict and add a new neck or head I guess.