1 citations · 1 across the 4 of their papers we have counts for
10 papers
AIMusicGuru: Music Assisted Human Pose Correction
Snehesh Shrestha, Cornelia Fermüller, Tianyu Huang +4
Pose Estimation techniques rely on visual cues available through observations represented in the form of pixels. But the performance is bounded by the frame rate of the video and s…
DiffPoseNet: Direct Differentiable Camera Pose Estimation
Chethan M. Parameshwara, Gokul Hari, Cornelia Fermüller +2
Current deep neural network approaches for camera pose estimation rely on scene structure for 3D motion estimation, but this decreases the robustness and thereby makes cross-datase…
GradTac: Spatio-Temporal Gradient Based Tactile Sensing
Kanishka Ganguly, Pavan Mantripragada, Chethan M. Parameshwara +3
Tactile sensing for robotics is achieved through a variety of mechanisms, including magnetic, optical-tactile, and conductive fluid. Currently, the fluid-based sensors have struck…
NudgeSeg: Zero-Shot Object Segmentation by Repeated Physical Interaction
Chahat Deep Singh, Nitin J. Sanket, Chethan M. Parameshwara +2
Recent advances in object segmentation have demonstrated that deep neural networks excel at object segmentation for specific classes in color and depth images. However, their perfo…
EVPropNet: Detecting Drones By Finding Propellers For Mid-Air Landing And Following
Nitin J. Sanket, Chahat Deep Singh, Chethan M. Parameshwara +3
The rapid rise of accessibility of unmanned aerial vehicles or drones pose a threat to general security and confidentiality. Most of the commercially available or custom-built dron…
SpikeMS: Deep Spiking Neural Network for Motion Segmentation
Chethan M. Parameshwara, Simin Li, Cornelia Fermüller +3
Spiking Neural Networks (SNN) are the so-called third generation of neural networks which attempt to more closely match the functioning of the biological brain. They inherently enc…