most citedInference, Learning and Attention Mechanisms that Exploit and Preserve Sparsity in Convolutional Networks

9 citations · 9 across the 1 of their papers we have counts for

collaborators

2 papers

cs.CV2018★ 9 cited

Inference, Learning and Attention Mechanisms that Exploit and Preserve Sparsity in Convolutional Networks

Timo Hackel, Mikhail Usvyatsov, Silvano Galliani +2

While CNNs naturally lend themselves to densely sampled data, and sophisticated implementations are available, they lack the ability to efficiently process sparse data. In this wor…

cs.CV2017

Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark

Timo Hackel, Nikolay Savinov, Lubor Ladicky +3

This paper presents a new 3D point cloud classification benchmark data set with over four billion manually labelled points, meant as input for data-hungry (deep) learning methods.…