Comments (3)
Hi @XXXVincent ,
You can use the 3D transformation in the dataset to transform the 3D LiDAR points to the sensor coordinate of the camera sensor, and then you can use the camera intrinsics to project the points to 2D depth images.
Best,
Juan-Ting Lin
from radar_depth.
@brade31919 Thank you for the earlier reply. Does this mean that the ground truth images are quite sparse?
from radar_depth.
Hi @isht7
Yes, this is the situation for outdoor self-driving datasets. Currently, people rely on LiDAR sensor to collect the ground truths. Same for Kitti or Waymo datasets
from radar_depth.
Related Issues (19)
- Awesome! HOT 1
- Release date HOT 13
- About ver2 in code HOT 2
- Questions about hyperparameters and processed dataset HOT 7
- Question on the RGB - Radar alignment issue HOT 5
- Bidirectional radar sweeps HOT 2
- About train / val scene numbers HOT 2
- Own dataset make method HOT 2
- Without lidar HOT 5
- Evaluation error args = checkpoint['args'] HOT 7
- Visualization HOT 1
- About the pretrained argument HOT 2
- Can not evaluate provided pretrained models HOT 1
- Question about ref_chan in radar multisweep HOT 1
- max_depth or max-depth?
- can you release your dataset? HOT 1
- Evaluation of Pretrained Models
- Detailed documentation for the processed dataset.
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from radar_depth.