# DAVIDSTUTZ

Check out the latest superpixel benchmark — Superpixel Benchmark (2016) — and let me know your opinion! @david_stutz
06thMARCH2017

Experiments show that this approach outperforms the 3D ShapeNets proposed by Wu et al. [1] as well as several baselines based on geometric hand-crafted features. They also try to reason why this simple approach outperforms convolutional neural networks applied directly to the volume. In particular, they account this difference in performance to the low resolution used for volumetric convolutional neural networks (usually around $32^3$).