Comments (1)
Hello @libenchong,
That's right, in training, we only shuffle in-city to maximise the percentage of informative pairs/triplets. You have the option in the code to shuffle all place. The training might take longer to achieve the same performance. If you are interested in squeezing the maximum information with informative batch sampling, take a look at our BMVC paper: https://bmvc2022.mpi-inf.mpg.de/958/
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Related Issues (20)
- Some questions in the reproduction process HOT 3
- About training and migration HOT 7
- Datasets construction HOT 1
- some questions about this experiments HOT 1
- Using the model
- Dataset image "panoid" generation rules HOT 1
- Dataset query image generation rule HOT 4
- about running problem HOT 2
- LICENSE HOT 1
- about aggregators
- A Question About Batch-Sizes
- pitts dataset
- What is the full name of "GSV"? HOT 1
- No Implementation of ConvAP module HOT 1
- lacking of MSLS files
- main.py's bug? HOT 8
- SPED and
- SPED and Nordland dataset HOT 4
- release pre-trained model HOT 1
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