7 citations · 7 across the 4 of their papers we have counts for
9 papers · 1 filter
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…
Topology-Aware Non-Rigid Point Cloud Registration
Konstantinos Zampogiannis, Cornelia Fermuller, Yiannis Aloimonos
In this paper, we introduce a non-rigid registration pipeline for pairs of unorganized point clouds that may be topologically different. Standard warp field estimation algorithms,…
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…
Evenly Cascaded Convolutional Networks
Chengxi Ye, Chinmaya Devaraj, Michael Maynord +2
We introduce Evenly Cascaded convolutional Network (ECN), a neural network taking inspiration from the cascade algorithm of wavelet analysis. ECN employs two feature streams - a lo…
Extracting Contact and Motion from Manipulation Videos
Konstantinos Zampogiannis, Kanishka Ganguly, Cornelia Fermuller +1
When we physically interact with our environment using our hands, we touch objects and force them to move: contact and motion are defining properties of manipulation. In this paper…
cilantro: A Lean, Versatile, and Efficient Library for Point Cloud Data Processing
Konstantinos Zampogiannis, Cornelia Fermuller, Yiannis Aloimonos
We introduce cilantro, an open-source C++ library for geometric and general-purpose point cloud data processing. The library provides functionality that covers low-level point clou…