54 citations · 98 across the 35 of their papers we have counts for
7 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…
Gluing Neural Networks Symbolically Through Hyperdimensional Computing
Peter Sutor, Dehao Yuan, Douglas Summers-Stay +2
Hyperdimensional Computing affords simple, yet powerful operations to create long Hyperdimensional Vectors (hypervectors) that can efficiently encode information, be used for learn…
EVIMO2: An Event Camera Dataset for Motion Segmentation, Optical Flow, Structure from Motion, and Visual Inertial Odometry in Indoor Scenes with Monocular or Stereo Algorithms
Levi Burner, Anton Mitrokhin, Cornelia Fermüller +1
A new event camera dataset, EVIMO2, is introduced that improves on the popular EVIMO dataset by providing more data, from better cameras, in more complex scenarios. As with its pre…
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…