Here we provide the baseline model (MTR) and our models' checkpoint.
We provide three types of models based on how much training data they had used:
5%
MTR's performance (epoch_28):
Waymo mAP minADE minFDE MissRate
VEHICLE 0.3288, 0.9097, 1.8636, 0.2156,
PEDESTRIAN 0.3192, 0.4202, 0.8957, 0.1134,
CYCLIST 0.2250, 0.9298, 1.9409, 0.2736,
Avg 0.2910, 0.7532, 1.5668, 0.2008,
LLM-Augmented-MTR's performance (epoch_28):
Waymo mAP minADE minFDE MissRate
VEHICLE 0.3367, 0.9216, 1.8960, 0.2236,
PEDESTRIAN 0.3613, 0.4295, 0.9059, 0.1103,
CYCLIST 0.2135, 0.9166, 1.9246, 0.2693,
Avg 0.3038, 0.7559, 1.5755, 0.2011,
20%
MTR's performance (epoch_29):
Waymo mAP minADE minFDE MissRate
VEHICLE 0.3912, 0.8239, 1.6778, 0.1800,
PEDESTRIAN 0.3608, 0.3829, 0.8091, 0.0935,
CYCLIST 0.2975, 0.8020, 1.6448, 0.2230,
Avg 0.3499, 0.6696, 1.3772, 0.1655,
LLM-Augmented-MTR's performance (epoch_29):
Waymo mAP minADE minFDE MissRate
VEHICLE 0.4028, 0.8090, 1.5943, 0.1711,
PEDESTRIAN 0.3621, 0.3880, 0.8107, 0.0958,
CYCLIST 0.2930, 0.8415, 1.7036, 0.2430,
Avg 0.3527, 0.6795, 1.3695, 0.1700,
100%
MTR's performance (epoch_30):
Waymo mAP minADE minFDE MissRate
VEHICLE 0.4464, 0.7545, 1.5161, 0.1523,
PEDESTRIAN 0.4149, 0.3456, 0.7252, 0.0750,
CYCLIST 0.3933, 0.6849, 1.3869, 0.1795,
Avg 0.4182, 0.5950, 1.2094, 0.1356,
LLM-Augmented-MTR's performance (epoch_26):
Waymo mAP minADE minFDE MissRate
VEHICLE 0.4578, 0.7570, 1.5308, 0.1523,
PEDESTRIAN 0.4794, 0.3535, 0.7376, 0.0765,
CYCLIST 0.3434, 0.7062, 1.4260, 0.1827,
Avg 0.4269, 0.6056, 1.2315, 0.1371,
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