Comments (2)
Hi @CaiYingFeng, the results in Table 2 are all done using WPCA4096. The only results that use WPCA512 in the paper are those in Figure 4. Try running Single Spatial but with WPCA4096 and that should fix the numbers. As to Spatial being better than RANSAC, we did notice that can happen in some datasets.
from patch-netvlad.
Also, in addition to Stephen's comments, we re-trained the network for the public code release and there might be minor deviations in the results obtained using the new network with those from what is reported in the paper (we checked that they are generally <1% difference in recall, sometimes they are slightly better than what is reported in the paper, sometimes slightly worse).
Feel free to re-open if you have further questions @CaiYingFeng.
from patch-netvlad.
Related Issues (20)
- cannot find the datasets... HOT 3
- How to arrange the mapillary dataset when training the code HOT 6
- How to get the value of Extended CMU Seasons? HOT 5
- Small issue on feature_match HOT 1
- Loss function HOT 1
- problem on training HOT 6
- Remove the WPCA layer before train HOT 4
- Support MPS
- How about the training time-consuming of hard samples mining module? HOT 3
- how to make a custom dataset? HOT 1
- Qustion about the function get_integral_feature(feat_in) HOT 2
- Cross-match between patches HOT 2
- questions about grouth.npz HOT 2
- How recalls on MSLS, Robotcar seasons, and CMU seasons are produced? HOT 6
- Ambiguity in the reported results
- patchnetvlad recall HOT 1
- pittsburgh_WPCA4096 HOT 1
- Tokyo24/7 HOT 1
- Large time taken for feature matching between query and database images for pitts30k HOT 5
- Unable to download pretrained models HOT 1
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from patch-netvlad.