Comments (1)
spyflying
commented on June 12, 2024
It is merely a technical trick to assign labels according to anchors or proposals. Since the output predictions from the initial iteration do not fit well with the 3d lanes, we assign their labels according to the associated anchors for training stability. For the iterative predictions, they are generated based on predictions from the previous iteration and already fit well with the 3d lanes, thus we assign their labels directly according to the predicted proposals.
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Related Issues (20)
- Unsatisfactory effect HOT 1
- How to evaluate on multiple gpus ？ HOT 2
- 关于ONCE数据集
- 使用openlane.py脚本划分Openlane 数据集问题 HOT 6
- Where is the code of "Optimization with Equal-Width Constraint"? HOT 1
- pytorch2onnx HOT 3
- GPU resource HOT 1
- 使用once.py划分ONCE数据集问题 HOT 2
- GPU resources when testing? HOT 1
- openlane数据集训练 HOT 4
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- AttributeError
- Segmentation fault(core dumped) when running the “train.py” HOT 2
- What is the version of geffnet?
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- Error occured while reproducing result HOT 1
- 关于等宽约束的问题 HOT 1
- ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: -11) local_rank: 0 (pid: 1416) of binary: HOT 1
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