Comments (6)
KevinDuBl
commented on August 12, 2024
1
You are really a hardworking and enthusiastic man. Thank you very much! Hope you will get good results on NeurIPS 2022!
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jihanyang
commented on August 12, 2024
No. They are not shared as the explained in this work: https://papers.nips.cc/paper/2019/hash/fd2c5e4680d9a01dba3aada5ece22270-Abstract.html.
BTW, I will support DSNorm and SASD officially soon.
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KevinDuBl
commented on August 12, 2024
In this paper, it's shared:
I'm very puzzled about this.
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KevinDuBl
commented on August 12, 2024
Well, it's a good news that DSNorm and SASD will release officially, thank you very much!
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jihanyang
commented on August 12, 2024
Sorry, I should say: they are shared. That's a typo.
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jihanyang
commented on August 12, 2024
Supported. You can have a try on it. However, as DSNorm and SASD are designed more for small objects such as pedestrian and cyclist. It might not show significant improvment on Car.
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Related Issues (20)
- Pretrain on waymo data HOT 2
- About pretrained weights for ST3D++ - PVRCNN HOT 1
- Evaluation on Lyft for paper result HOT 2
- Question about pretrained model HOT 1
- Unstable performance HOT 4
- Source Only and SN training HOT 13
- Have you ever tried ST3D on PointPillars? HOT 2
- Can this project be implement in openpdet-v0.6 HOT 10
- AttributeError: 'DataAugmentor' object has no attribute 'random_object_scaling' HOT 9
- AttributeError: 'EasyDict' object has no attribute 'FOV_DEGREE' HOT 4
- The Car [email protected], 0.70, 0.70 IS 0
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- Performance of Nuscenes2KITTI HOT 3
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- RecursionError: maximum recursion depth exceeded while calling a Python object HOT 2
- what is the purpose of data augmentation in the target domain? HOT 4
- How to set source batch and target batch to fetch data as the data order in ImageSets.
- The config file for multi classes training
- attempt to write config kitti -> nuscenes(mini)
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