1 citations · 1 across the 4 of their papers we have counts for
5 papers
A Consistency-Based Loss for Deep Odometry Through Uncertainty Propagation
Hamed Damirchi, Rooholla Khorrambakht, Hamid D. Taghirad +1
The incremental poses computed through odometry can be integrated over time to calculate the pose of a device with respect to an initial location. The resulting global pose may be…
Deep Inertial Odometry with Accurate IMU Preintegration
Rooholla Khorrambakht, Chris Xiaoxuan Lu, Hamed Damirchi +2
Inertial Measurement Units (IMUs) are interceptive modalities that provide ego-motion measurements independent of the environmental factors. They are widely adopted in various auto…
Exploring Self-Attention for Visual Odometry
Hamed Damirchi, Rooholla Khorrambakht, Hamid D. Taghirad
Visual odometry networks commonly use pretrained optical flow networks in order to derive the ego-motion between consecutive frames. The features extracted by these networks repres…
ARC-Net: Activity Recognition Through Capsules
Hamed Damirchi, Rooholla Khorrambakht, Hamid Taghirad
Human Activity Recognition (HAR) is a challenging problem that needs advanced solutions than using handcrafted features to achieve a desirable performance. Deep learning has been p…
IMU Preintegrated Features for Efficient Deep Inertial Odometry
R. Khorrambakht, H. Damirchi, H. D. Taghirad
MEMS Inertial Measurement Units (IMUs) as ubiquitous proprioceptive motion measurement devices are available on various everyday gadgets and robotic platforms. Nevertheless, the di…