Data Preparation
June 6, 2025 · View on GitHub
Download the M3CAD dataset from Google Drive. The dataset contains 204 scenes with a total size of 120 GB.
After downloading, please organize the data following this directory structure:
data/
├── infos/
└── m3cad_carla_ue5/
├── maps/
│ ├── expansion/
│ ├── Town01.png
│ ├── Town02.png
│ ├── Town03.png
│ ├── Town04.png
│ ├── Town05.png
│ ├── Town06.png
│ ├── Town07.png
│ └── Town10HD.png
├── others/
│ └── m3cad_uniad_motion_anchor_infos_mode6.pkl
├── samples/
│ ├── CAM_BACK/
│ ├── CAM_LEFT/
│ ├── CAM_RIGHT/
│ ├── CAM_FRONT/
│ └── LiDAR_TOP/
├── v1.0-trainval/
│ ├── attribute.json
│ ├── category.json
│ ├── log.json
│ ├── map.json
│ ├── sample_annotation.json
│ ├── sensor.json
│ ├── visibility.json
│ ├── ego_pose.json
│ ├── instance.json
│ ├── calibrated_sensor.json
│ ├── sample_data.json
│ ├── sample.json
│ └── scene.json
└── v1.0-test/
Train/Val/Test Split
We provide the train/val/test split of M3CAD dataset in splits.py (located in submodules/nuscenes-devkit/python-sdk/nuscenes/utils/splits.py).
train = [
# Timestamp: 2025_06_24_18_33_22
'2025_06_24_18_33_22_60', '2025_06_24_18_33_22_51', '2025_06_24_18_33_22_75',
# Timestamp: 2025_03_03_15_02_55
'2025_03_03_15_02_55_51', '2025_03_03_15_02_55_50', '2025_03_03_15_02_55_37',
# Timestamp: 2025_07_01_18_22_24
'2025_07_01_18_22_24_75', '2025_07_01_18_22_24_60', '2025_07_01_18_22_24_51',
# Timestamp: 2025_03_03_19_46_59
'2025_03_03_19_46_59_37', '2025_03_03_19_46_59_47', '2025_03_03_19_46_59_25',
# Timestamp: 2025_03_03_17_27_46
'2025_03_03_17_27_46_25', '2025_03_03_17_27_46_37',
# Timestamp: 2025_03_03_17_43_14
'2025_03_03_17_43_14_25', '2025_03_03_17_43_14_37', '2025_03_03_17_43_14_47',
# Timestamp: 2025_03_03_20_26_07
'2025_03_03_20_26_07_47', '2025_03_03_20_26_07_51', '2025_03_03_20_26_07_37', '2025_03_03_20_26_07_50',
# Timestamp: 2025_06_07_23_42_19
'2025_06_07_23_42_19_85', '2025_06_07_23_42_19_75', '2025_06_07_23_42_19_81',
# Timestamp: 2025_03_03_16_08_34
'2025_03_03_16_08_34_47', '2025_03_03_16_08_34_37', '2025_03_03_16_08_34_50', '2025_03_03_16_08_34_25',
# Timestamp: 2025_05_27_14_08_01
'2025_05_27_14_08_01_60', '2025_05_27_14_08_01_50', '2025_05_27_14_08_01_51',
# Timestamp: 2025_03_03_15_35_50
'2025_03_03_15_35_50_37', '2025_03_03_15_35_50_25', '2025_03_03_15_35_50_47',
# Timestamp: 2025_03_03_19_35_10
'2025_03_03_19_35_10_47', '2025_03_03_19_35_10_25', '2025_03_03_19_35_10_50', '2025_03_03_19_35_10_37',
# Timestamp: 2025_06_22_18_33_22
'2025_06_22_18_33_22_51', '2025_06_22_18_33_22_60', '2025_06_22_18_33_22_75',
# Timestamp: 2025_03_03_18_13_10
'2025_03_03_18_13_10_37', '2025_03_03_18_13_10_50', '2025_03_03_18_13_10_47', '2025_03_03_18_13_10_51',
# Timestamp: 2025_03_03_16_22_16
'2025_03_03_16_22_16_47', '2025_03_03_16_22_16_25', '2025_03_03_16_22_16_37',
# Timestamp: 2025_03_03_15_17_51
'2025_03_03_15_17_51_51', '2025_03_03_15_17_51_47', '2025_03_03_15_17_51_50', '2025_03_03_15_17_51_37',
# Timestamp: 2025_07_11_09_04_49
'2025_07_11_09_04_49_75', '2025_07_11_09_04_49_60', '2025_07_11_09_04_49_51',
# Timestamp: 2025_03_03_20_19_40
'2025_03_03_20_19_40_37', '2025_03_03_20_19_40_25', '2025_03_03_20_19_40_47',
# Timestamp: 2025_03_03_17_32_03
'2025_03_03_17_32_03_37', '2025_03_03_17_32_03_47', '2025_03_03_17_32_03_25',
# Timestamp: 2025_06_29_12_50_21
'2025_06_29_12_50_21_50', '2025_06_29_12_50_21_60', '2025_06_29_12_50_21_51',
# Timestamp: 2025_03_03_19_02_35
'2025_03_03_19_02_35_37', '2025_03_03_19_02_35_50', '2025_03_03_19_02_35_47', '2025_03_03_19_02_35_25',
# Timestamp: 2025_03_03_14_52_14
'2025_03_03_14_52_14_37', '2025_03_03_14_52_14_51', '2025_03_03_14_52_14_47',
# Timestamp: 2025_05_26_14_08_01
'2025_05_26_14_08_01_51', '2025_05_26_14_08_01_60', '2025_05_26_14_08_01_50',
# Timestamp: 2025_03_03_16_56_12
'2025_03_03_16_56_12_37', '2025_03_03_16_56_12_50', '2025_03_03_16_56_12_47',
# Timestamp: 2025_03_03_18_08_10
'2025_03_03_18_08_10_25', '2025_03_03_18_08_10_47', '2025_03_03_18_08_10_37', '2025_03_03_18_08_10_50',
# Timestamp: 2025_06_12_10_31_09
'2025_06_12_10_31_09_60', '2025_06_12_10_31_09_75', '2025_06_12_10_31_09_51',
# Timestamp: 2025_03_03_15_05_32
'2025_03_03_15_05_32_37', '2025_03_03_15_05_32_51', '2025_03_03_15_05_32_47', '2025_03_03_15_05_32_50',
# Timestamp: 2025_05_31_09_26_05
'2025_05_31_09_26_05_51', '2025_05_31_09_26_05_75', '2025_05_31_09_26_05_60',
# Timestamp: 2025_03_03_16_06_25
'2025_03_03_16_06_25_47', '2025_03_03_16_06_25_37', '2025_03_03_16_06_25_25',
# Timestamp: 2025_03_03_17_05_14
'2025_03_03_17_05_14_25', '2025_03_03_17_05_14_47',
# Timestamp: 2025_03_03_20_40_30
'2025_03_03_20_40_30_50', '2025_03_03_20_40_30_51', '2025_03_03_20_40_30_47', '2025_03_03_20_40_30_37',
# Timestamp: 2025_03_03_19_26_56
'2025_03_03_19_26_56_25', '2025_03_03_19_26_56_47', '2025_03_03_19_26_56_37',
# Timestamp: 2025_03_03_15_11_06
'2025_03_03_15_11_06_50', '2025_03_03_15_11_06_47', '2025_03_03_15_11_06_51', '2025_03_03_15_11_06_37',
# Timestamp: 2025_07_07_08_53_39
'2025_07_07_08_53_39_75', '2025_07_07_08_53_39_60', '2025_07_07_08_53_39_51',
# Timestamp: 2025_03_03_17_18_27
'2025_03_03_17_18_27_50', '2025_03_03_17_18_27_37', '2025_03_03_17_18_27_47', '2025_03_03_17_18_27_51',
# Timestamp: 2025_06_04_18_44_22
'2025_06_04_18_44_22_60', '2025_06_04_18_44_22_50', '2025_06_04_18_44_22_51',
# Timestamp: 2025_03_03_19_42_20
'2025_03_03_19_42_20_50', '2025_03_03_19_42_20_37', '2025_03_03_19_42_20_47', '2025_03_03_19_42_20_25',
# Timestamp: 2025_03_03_16_15_53
'2025_03_03_16_15_53_37', '2025_03_03_16_15_53_47', '2025_03_03_16_15_53_25',
# Timestamp: 2025_05_30_09_26_05
'2025_05_30_09_26_05_60', '2025_05_30_09_26_05_51', '2025_05_30_09_26_05_75',
# Timestamp: 2025_03_03_20_00_30
'2025_03_03_20_00_30_47', '2025_03_03_20_00_30_25',
# Timestamp: 2025_03_03_16_36_16
'2025_03_03_16_36_16_47', '2025_03_03_16_36_16_50', '2025_03_03_16_36_16_51',
# Timestamp: 2025_03_03_17_23_10
'2025_03_03_17_23_10_47', '2025_03_03_17_23_10_37', '2025_03_03_17_23_10_25',
# Timestamp: 2025_06_02_18_44_22
'2025_06_02_18_44_22_60', '2025_06_02_18_44_22_50', '2025_06_02_18_44_22_51',
# Timestamp: 2025_03_03_19_09_29
'2025_03_03_19_09_29_37', '2025_03_03_19_09_29_25', '2025_03_03_19_09_29_47',
# Timestamp: 2025_07_05_14_39_47
'2025_07_05_14_39_47_60', '2025_07_05_14_39_47_51', '2025_07_05_14_39_47_50',
]
val = [
# Timestamp: 2025_03_03_15_30_41
'2025_03_03_15_30_41_25', '2025_03_03_15_30_41_50', '2025_03_03_15_30_41_47',
# Timestamp: 2025_03_03_21_08_04
'2025_03_03_21_08_04_51', '2025_03_03_21_08_04_50', '2025_03_03_21_08_04_37',
# Timestamp: 2025_03_03_18_58_40
'2025_03_03_18_58_40_37', '2025_03_03_18_58_40_47', '2025_03_03_18_58_40_25',
# Timestamp: 2025_03_03_19_05_10
'2025_03_03_19_05_10_47', '2025_03_03_19_05_10_37', '2025_03_03_19_05_10_25',
# Timestamp: 2025_03_03_16_00_01
'2025_03_03_16_00_01_37', '2025_03_03_16_00_01_25', '2025_03_03_16_00_01_47',
# Timestamp: 2025_03_03_19_49_04
'2025_03_03_19_49_04_50', '2025_03_03_19_49_04_25', '2025_03_03_19_49_04_37', '2025_03_03_19_49_04_47',
# Timestamp: 2025_06_03_18_44_22
'2025_06_03_18_44_22_60', '2025_06_03_18_44_22_50', '2025_06_03_18_44_22_51',
# Timestamp: 2025_05_24_14_08_01
'2025_05_24_14_08_01_60', '2025_05_24_14_08_01_50', '2025_05_24_14_08_01_51',
# Timestamp: 2025_03_03_15_28_34
'2025_03_03_15_28_34_25', '2025_03_03_15_28_34_47', '2025_03_03_15_28_34_37',
# Timestamp: 2025_03_03_20_21_46
'2025_03_03_20_21_46_37', '2025_03_03_20_21_46_47',
]
test = [
# Timestamp: 2025_03_03_14_54_49
'2025_03_03_14_54_49_47', '2025_03_03_14_54_49_37', '2025_03_03_14_54_49_50', '2025_03_03_14_54_49_51',
# Timestamp: 2025_03_03_17_45_21
'2025_03_03_17_45_21_25', '2025_03_03_17_45_21_37', '2025_03_03_17_45_21_47', '2025_03_03_17_45_21_50',
# Timestamp: 2025_06_11_10_31_09
'2025_06_11_10_31_09_51', '2025_06_11_10_31_09_60', '2025_06_11_10_31_09_75',
# Timestamp: 2025_07_02_06_03_04
'2025_07_02_06_03_04_85', '2025_07_02_06_03_04_75', '2025_07_02_06_03_04_81',
# Timestamp: 2025_03_03_17_07_25
'2025_03_03_17_07_25_25', '2025_03_03_17_07_25_47', '2025_03_03_17_07_25_50', '2025_03_03_17_07_25_37',
# Timestamp: 2025_05_29_10_09_36
'2025_05_29_10_09_36_60', '2025_05_29_10_09_36_75', '2025_05_29_10_09_36_51',
# Timestamp: 2025_03_03_16_11_05
'2025_03_03_16_11_05_47', '2025_03_03_16_11_05_50', '2025_03_03_16_11_05_37', '2025_03_03_16_11_05_51',
# Timestamp: 2025_06_23_18_33_22
'2025_06_23_18_33_22_51', '2025_06_23_18_33_22_75', '2025_06_23_18_33_22_60',
# Timestamp: 2025_03_03_18_43_56
'2025_03_03_18_43_56_47', '2025_03_03_18_43_56_25',
]