9 citations · 26 across the 13 of their papers we have counts for
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cs.CV2019★ 4 cited
Tabulated MLP for Fast Point Feature Embedding
Yusuke Sekikawa, Teppei Suzuki
Aiming at a drastic speedup for point-data embeddings at test time, we propose a new framework that uses a pair of multi-layer perceptron (MLP) and look-up table (LUT) to transform…
cs.CV2019★ 3 cited
Adversarial Transformations for Semi-Supervised Learning
Teppei Suzuki, Ikuro Sato
We propose a Regularization framework based on Adversarial Transformations (RAT) for semi-supervised learning. RAT is designed to enhance robustness of the output distribution of c…