4 papers
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…