Hi, great job on this work!
I have been trying to test BBC dataset using only place feature (generated using pre/place/extract_feat.py) with place LGSS model you provide but got much worse results (AP around 40) than your paper (AP 79.5). I understand that the AP score mentioned in your paper was probably generated using all four features as well as global optimization. But I still expect using only place feature performs better than what I got. Do you know where I could be wrong?
Another question is BBC dataset provides 5 sets of ground truth labels, which one did you use in your evaluation?
Thanks a lot
Hi, great job on this work!
I have been trying to test BBC dataset using only place feature (generated using pre/place/extract_feat.py) with place LGSS model you provide but got much worse results (AP around 40) than your paper (AP 79.5). I understand that the AP score mentioned in your paper was probably generated using all four features as well as global optimization. But I still expect using only place feature performs better than what I got. Do you know where I could be wrong?
Another question is BBC dataset provides 5 sets of ground truth labels, which one did you use in your evaluation?
Thanks a lot