406 citations · 983 across the 27 of their papers we have counts for
3 papers · 2 filters
ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation
Francesco Visin, Marco Ciccone, Adriana Romero +5
We propose a structured prediction architecture, which exploits the local generic features extracted by Convolutional Neural Networks and the capacity of Recurrent Neural Networks…
Efficient moving point handling for incremental 3D manifold reconstruction
Andrea Romanoni, Matteo Matteucci
As incremental Structure from Motion algorithms become effective, a good sparse point cloud representing the map of the scene becomes available frame-by-frame. From the 3D Delaunay…
ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks
Francesco Visin, Kyle Kastner, Kyunghyun Cho +3
In this paper, we propose a deep neural network architecture for object recognition based on recurrent neural networks. The proposed network, called ReNet, replaces the ubiquitous…