Comments (2)
@miaozhang97bosch
Your concern is valuable. We use [x, y, z] as the cross-domain setting (such as Uni3D and Bi3D) for alignment with previous research work, such as ST3D. However, we also believe that intensity is important for distinguishing different objects obtained using LiDAR. Therefore, it may be beneficial to conduct cross-domain research that includes the intensity for the cross-domain 3D object detection.
Additionally, since AD-PT is the first work to study how pre-trained model parameters can be fine-tuned to different datasets, we adopted the experimental setting of [x, y, z, intensity] (or [x, y, z, intensity, elongation] for Waymo), utilizing all the information obtained from the employed LiDAR.
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Got it. Thanks for your reply.
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Related Issues (20)
- About ReSimAD HOT 2
- The installation of gcc-5.4.0 HOT 1
- TypeError: __init__() missing 3 required positional arguments: 'num_class_s2', 'dataset_s2', and 'source_one_name'[] HOT 1
- Using the merge_labels.py file HOT 7
- Pretraining on NuScenes HOT 1
- KeyError: "param 'initial_lr' is not specified in param_groups[0] when resuming an optimizer" HOT 4
- Running pre-training script with point contrast HOT 3
- Using ckpt for pretraining HOT 4
- Creating Waymo infos using huge amounts of ram HOT 1
- How should I use Uni3D to train multiple datasets? HOT 2
- Why is SHIFT_COOR set to [0.0, 0.0, 1.6] in KITTI? HOT 2
- Question About AD-PT HOT 2
- Waymo evaluation issue HOT 6
- Questions on detection heads of Uni3D HOT 4
- Questions on Training Uni3D HOT 5
- Quick Squence Demo for 3DTrans ( KITTI / Waymo) HOT 1
- Fine-tuning on Waymo-Kitti HOT 1
- Question on generalization study on Uni3D HOT 1
- Problem about GPU memory HOT 1
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