denoise-imu-gyro
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mbrossar
Convolutional Neural Networks for Denoising Gyroscopes of Low-Cost IMUs
Hi, I downloaded your pre-trained model on TUM-VI and evaluated it by the toolbox provided by https://github.com/uzh-rpg/rpg_trajectory_evaluation, which is also recommended by open-vins (https://docs.openvins.com/namespaceov__eval.html). The AOE results for rooms 2,...
Hey, I tried to validate the results on two other datasets, the StructVIO dataset, and the ADVIO dataset. Have you guys tried to validate the results on any other datasets?...
Hello Brossar and thanks for sharing your work. I'm trying to use your method with a different dataset. In order to train and test the network - it seems like...
Hello, may I ask why are `self.N0` predictions from the network removed, when computing the loss during training? My guess is this should account for the initial padding, but why...
Hello. Thanks for your code. Do you have a pretrained model for your experiment? I thought it could be mentioned in **Testing** here `Download optimized parameters at this url, extract...
Hi Mr.Brossard, I'm very interested in your paper called Denoising IMU Gyroscopes with Deep Learning for Open-Loop Attitude Estimation. I have a little question. In your paper,the rotation matrix Rn...
I tried running this on Linux per the instructions, but with the cpu-only version of Torch. That still gives me the NVIDIA error: `RuntimeError: Found no NVIDIA driver on your...
Hello, First of all, thank you for your work (paper + code), it's very well explained and the approach looks elegant. I would like to push the work further by...
Has anyone reproduced the results of the TUM-VI room_4 raw IMU data, it doesn't seem to be as bad as Fig.6 in the papaer.
