6 citations · 8 across the 11 of their papers we have counts for
8 papers · 1 filter
WorldGen: A Large Scale Generative Simulator
Chahat Deep Singh, Riya Kumari, Cornelia Fermüller +2
In the era of deep learning, data is the critical determining factor in the performance of neural network models. Generating large datasets suffers from various difficulties such a…
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…
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…
PRGFlow: Benchmarking SWAP-Aware Unified Deep Visual Inertial Odometry
Nitin J. Sanket, Chahat Deep Singh, Cornelia Fermüller +1
Odometry on aerial robots has to be of low latency and high robustness whilst also respecting the Size, Weight, Area and Power (SWAP) constraints as demanded by the size of the rob…