Comments (3)
Hello, may I ask, in the paper, the training is carried out in two stages, but in the code at that time, the training is carried out in three stages, why? How do they correspond to each other
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Could you leave a contact information? I want to ask you some questions
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Query-based methods are less stable than anchor-based methods, and THUMOS14 is a tiny dataset.
So we think a 0.5% gap is acceptable.
You can re-run the experiment several times and may get a better result.
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Related Issues (20)
- RTD code for ActivityNet-1.3 HOT 4
- from datasets import build_dataset ;from models import build_model HOT 1
- I have a problem HOT 1
- A question about reproducibility~
- a question for training HOT 1
- TEM_scores HOT 5
- labe issue HOT 4
- about activitynet feature HOT 4
- about anet code HOT 4
- a problem HOT 2
- about thumos14 annotation HOT 3
- Hello, may I ask, in the paper, the training is carried out in two stages, but in the code at that time, the training is carried out in three stages, why? How do they correspond to each other HOT 2
- ActivityNet HOT 8
- ANet HOT 10
- about TEM HOT 1
- about RTD in Anet HOT 1
- temporal action detection HOT 1
- how to change the stride of THUMOS features
- WARNING:torch.distributed.elastic.agent.server.api:Received 2 death signal, shutting down workers WARNING:torch.distributed.elastic.multiprocessing.api:Sending process 4797 closing signal SIGINT
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