372 citations · 432 across the 6 of their papers we have counts for
6 papers
SceneCalib: Automatic Targetless Calibration of Cameras and Lidars in Autonomous Driving
Ayon Sen, Gang Pan, Anton Mitrokhin +1
Accurate camera-to-lidar calibration is a requirement for sensor data fusion in many 3D perception tasks. In this paper, we present SceneCalib, a novel method for simultaneous self…
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…
Network Deconvolution
Chengxi Ye, Matthew Evanusa, Hua He +5
Convolution is a central operation in Convolutional Neural Networks (CNNs), which applies a kernel to overlapping regions shifted across the image. However, because of the strong c…
EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras
Anton Mitrokhin, Chengxi Ye, Cornelia Fermuller +2
We present the first event-based learning approach for motion segmentation in indoor scenes and the first event-based dataset - EV-IMO - which includes accurate pixel-wise motion m…
Unsupervised Learning of Dense Optical Flow, Depth and Egomotion from Sparse Event Data
Chengxi Ye, Anton Mitrokhin, Cornelia Fermüller +2
In this work we present a lightweight, unsupervised learning pipeline for \textit{dense} depth, optical flow and egomotion estimation from sparse event output of the Dynamic Vision…
Event-based Moving Object Detection and Tracking
Anton Mitrokhin, Cornelia Fermuller, Chethan Parameshwara +1
Event-based vision sensors, such as the Dynamic Vision Sensor (DVS), are ideally suited for real-time motion analysis. The unique properties encompassed in the readings of such sen…