Evaluation of Pose about deep-sfm-revisited HOT 3 OPEN

Hi,

The default choice is the right one, since I have configured the flags in the kitti.yml. It filters the flow matches via SIFT Loc, and computes the pose using the filtered matches. The default one should have been '5-point' + ' Flow matches '+ 'SIFT Loc'.

I notice that some people report their RANSAC CUDA extension does not work well, which might be the reason for the wrong performance. Would you mind sharing your results (relative poses predicted by the network) of sequence 09? I may have a look at the results.

Best,
Jianyuan

from deep-sfm-revisited.

Hi! Thanks! Happy the Spring Festival !

Sorry for late reply. Following steps in issue #8 , I got the evaluation results. The translational error is 4.029%, the rotational error is 1.317 deg/100m, and ATE is as large as 61.888m.
sequence_09.pdf
Also, here are the relative poses predicted by the network of sequence 09, which contains all poses in one .npy file:
09_bw.zip
BTW, I have used the CUDA 10.2. Will that cause some problem? Thanks for help!

Best

from deep-sfm-revisited.

Happy the Spring Festival. I would have a look after coming back to the work. I guess I should clean the pose evaluation code and release it later.

from deep-sfm-revisited.