Comments (1)
Yes, you are right. Quoting what we wrote in Appendix A:
For nuScenes, we input all Lidar points within the half-second segments, and only train with point features at the last time stamp.
Before we released the wrong Lidar point clouds which are only the points on the last timestamp, so the input and output points are the same. Now, the new ones are all points of half-second segments as the input points (~300K points), which gives more information, and train only with the point features on the points of last timestamp (~30K points). We observed better performance in this way.
Best
Songyou
from openscene.
Related Issues (20)
- Feature fusion of nuScenes HOT 2
- Matterport Evaluation Error HOT 2
- Working with Frame parameters for Replica feature fusion HOT 4
- train on my own dataset HOT 1
- How to get the ".pt" file๏ผ HOT 1
- Multi-view fusion in nuscenes HOT 1
- How to get 'scene.ply' in nuScenes HOT 8
- Training Time HOT 1
- Inference speed on the nuScenes Lidarseg HOT 1
- Evaluation with "model.eval()" HOT 3
- "Unable to connection" error when running the demo HOT 1
- Failed to clone demo/gaps HOT 1
- Multiview fusion in nuScenes HOT 7
- Openseg feature HOT 1
- Could you share nuscenes_3d/train data ? HOT 2
- About the LSeg
- About LSeg feature HOT 1
- LSeg Feature and Evaluate HOT 2
- LSeg on ScanNet HOT 2
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