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Cross-view Supervised Learning
Hello,
my name is Ahmed me and some of my friends are working on a graduation project to develop a deep learning model to do localization based on top view and ground view of urban places. we would be thankful to let us have access to the data-set.
the size of the streetview image is 1232224, which is obviously cropped. Could you please share the complete streetview image, which is 1232616 in size and has not been cropped?
The email address of [email protected] can no longer be contacted.We look forward to your reply.
Can you share the image data before cutting the ground and sky parts?
Which version of Python are you used for this code?
Thank for sharing this code and how to predict ground-level panorama from an aerial-level image?
Hey @viibridges,
Thanks for your very nice and insightful work! We are doing some research highly related to your work, but we find the train/test files are missing. In addition, the link you provided for the dataset is also broken (404).
Hence, if it is possible, may I kindly ask you to share those files and the dataset again? And we promise everything will be used only for academic research.
Bests and thanks a lot,
Hello sir , I’d like to have a download link to the CVUSA dataset ,
but I can’t use the current one
http://mvrl.cs.uky.edu/datasets/cvusa/
due to missing “splits” directory,
and there are multiple dead links, specifically the subset used for localization evaluation.
Hi,
I'm not sure to understand the use of wa, wb, wc, wd in the interpolate function:
"
# channels dim
im_flat = tf.reshape(im, tf.stack([-1, channels]))
im_flat = tf.cast(im_flat, 'float32')
Ia = tf.gather(im_flat, idx_a)
Ib = tf.gather(im_flat, idx_b)
Ic = tf.gather(im_flat, idx_c)
Id = tf.gather(im_flat, idx_d)
wa = tf.expand_dims(((1-x+x0_f) * (1-y+y0_f)), 1)
wb = tf.expand_dims(((1-x+x0_f) * (1-y1_f+y)), 1)
wc = tf.expand_dims(((1-x1_f+x) * (1-y+y0_f)), 1)
wd = tf.expand_dims(((1-x1_f+x) * (1-y1_f+y)), 1)
output = tf.add_n([waIa, wbIb, wcIc, wdId])
"
Do you use the w as a weight which value depends on how far the sample pixel is from the true floating interpolated localization (x,y) ?
Hi
I am a graduate student from the University of Science and Technology of China. Thank you very much for your contributions in the field, and I am now reproducing this work. I got the data set according to the download link on github, but I can't find the split csv for training and testing, now I'm asking for your help!
Thank you for providing the repository and dataset. I tried downloading the dataset today but the link couldn't be openned . Is there another site/mirror I could get the dataset from?
Could you please share model weight for test?
the dataset did not work. how can we get access to that?
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