Comments (1)
I will close this task, I have seen that the fine window size in the Original LoFTR is 5x5 and in the EfficientLoFTR it is 8x8. Im guessing this in general means that the efficient LoFTR is capable of more accurate matches. Here is an example where i Rotated the images by 5°. You can see that both models are able to predict at fine level outside of the coarse level grid.
Original LoFTR with 5° rotation:
Efficient LoFTR with 5° rotation:
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Related Issues (20)
- how to produce poses and intrinsics HOT 1
- Training code release HOT 2
- Script for 2 camera demo HOT 2
- Training code HOT 2
- 训练时常 HOT 1
- Output descriptors HOT 2
- Indoor model weight HOT 2
- 速度对比 HOT 1
- looing forward to your training code HOT 4
- can it match two images in this project now? HOT 1
- generate high-quality point clouds HOT 3
- image size for training and Ablation Studies of Image Resolution HOT 4
- why did you use grayscale image? HOT 1
- Training Code HOT 1
- 导出onnx HOT 2
- 请问支持上传两张图片进行匹配吗?如果可以的话我应该怎么操作 HOT 1
- 训练代码
- x_mask and source_mask is None HOT 2
- The issue of code open source
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