DKM
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Parskatt
[CVPR 2023] DKM: Dense Kernelized Feature Matching for Geometry Estimation
Congratulations on the great work! Do you have plans for releasing the training code ? I'm thinking on fine-tuning your weights for more specific tasks.
Hello, may I ask if it's possible to use DKMv3 for training when there is no depth information in my own dataset? I only need to obtain the horizontal and...
Hello author, I wonder how you painted the Figure 4. Coordinate embeddings preserve multimodality in the main paper. Cause even use the coordinate as the GP output, the GP posterior...
The work is very exciting! I ask about the scaling process in the following code. Why divide by 4 here? Isn't ins * diaplacement[] supposed to restore to the original...
It's a great work!!! But I met some problem, when I ran your training code, the weights named "train_DKMv3_outdoor_latest.pth" was 852MB. However, the model you provided with the training code...
Great job! I do inference on 3090, it takes about 0.7 seconds to calculate the time of two images, and what other operations can be used for inference acceleration, in...
Thanks for your excellent work! May I ask for one possible solution for the problem shown as below? Thank you so much! > Traceback (most recent call last): > File...
I noticed that you use GC-RANSAC for pose estimation. I tried to look into the GC-RANSAC repository but couldn't get it to work. I was hoping to take a look...
Can you post that part of the code that works on the synthetic dataset? I want to try it on cross-spectrum
Why does PDC-net perform reasonably well in pck but much worse in two-view geometry estimation? pdc-net pck:    Is it because the confidence it predicts is learned self-supervised?...
