Comments (2)
hit2sjtu
commented on June 17, 2024
1
@amaralibey implementation for NetVLAD definitely is a plus
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amaralibey
commented on June 17, 2024
Hello @wpumain,
We have made available the code for testing on 8 different benchmarks (Tokyo 247 not included). To evaluate methods, you can utilize the provided pretrained weights and code available in the gsv-cities repository (https://github.com/amaralibey/gsv-cities/blob/main/notebooks/evaluate_model.ipynb).
Please note that currently we have not shared the weights and implementation for NetVLAD, but we may include them in future versions of the code.
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Related Issues (20)
- why is the skip connection executed inside the FeatureMixerLayer here? HOT 2
- Really a good work with simple but effective approach!
- Training loss and generalization during test HOT 4
- Just for testing HOT 2
- A singleGPU will run the results, but multiple GPUs will make an error！！ HOT 3
- optimizer step HOT 2
- question about backbone ‘Swin’ HOT 5
- Multi-similarity mining on Pittsburgh30k training set HOT 6
- how to change query image shape? HOT 1
- The error samples are due to issues with the ground truth annotations rather than errors in the model predictions. HOT 3
- Dataset HOT 4
- About the specific number of images of the Mapillary Challenge dataset
- would you release the resnet18 pretrained model?
- How to evaluate this model?
- Some questions
- About pitts30k_val.mat. I can not find it in PittsburgDataset HOT 1
- License File
- Releasing the model on torch.hub?
- On releasing the trained weights of ResNet50 with 2048 dimensionality.
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