From eed553fb45756ce5ea35418db77383732c444c42 Mon Sep 17 00:00:00 2001 From: Jiuhong Xiao Date: Tue, 18 Jun 2024 12:05:37 -0400 Subject: [PATCH] Update README.md --- README.md | 27 ++++++++++++++++++++++++++- 1 file changed, 26 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index e5da005..c1030d7 100644 --- a/README.md +++ b/README.md @@ -3,7 +3,12 @@ This is the official repository for STHN: Deep Homography Estimation for UAV Thermal Geo-localization with Satellite Imagery. ``` -bibtex TBD +@article{xiao2024sthn, + title={STHN: Deep Homography Estimation for UAV Thermal Geo-localization with Satellite Imagery}, + author={Xiao, Jiuhong and Zhang, Ning and Tortei, Daniel and Loianno, Giuseppe}, + journal={arXiv preprint arXiv:2405.20470}, + year={2024} +} ``` **Developer: Jiuhong Xiao
Affiliation: [NYU ARPL](https://wp.nyu.edu/arpl/)
@@ -112,6 +117,26 @@ For training and evaluating the image-matching baselines (anyloc and STGL), plea ## Pretrained Models Download pretrained models for $W_S=1536$ and $D_C=512$ m: [Download](https://drive.google.com/drive/folders/19Z0wqeDlJyzTZB1qc355G2WEww7I9rTB?usp=sharing) +## Additional Details +
+ Train/Val/Test split + Below is the visualization of the train-validation-test regions. The dataset includes thermal maps from six flights: three flights (conducted at 9 PM, 12 AM, and 2 AM) cover the upper region, and the other three flights (conducted at 10 PM, 1 AM, and 3 AM) cover the lower region. The lower region is further divided into training and validation subsets. The synthesized thermal images span a larger area (23,744m x 9,088m) but exclude the test region to assess generalization performance properly. + + ![image](https://github.com/arplaboratory/STHN/assets/29690116/8e833ba9-644e-4446-b951-7b17a5e4316b) + +
+
+ Architecture Details + + +
+ +
+ Direct Linear Transformation Details + In practice, we use kornia's implementation [kornia](https://kornia.readthedocs.io/en/stable/geometry.transform.html#kornia.geometry.transform.get_perspective_transform). + For more details, you can refer to [wiki](https://en.wikipedia.org/wiki/Direct_linear_transformation). + +
## Acknowledgement Our implementation refers to the following repositories and appreciate their excellent work.