6 citations · 6 across the 4 of their papers we have counts for
12 papers
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…
MorphEyes: Variable Baseline Stereo For Quadrotor Navigation
Nitin J. Sanket, Chahat Deep Singh, Varun Asthana +2
Morphable design and depth-based visual control are two upcoming trends leading to advancements in the field of quadrotor autonomy. Stereo-cameras have struck the perfect balance o…